How To Make An Infinitely Scalable RDBMS

http://highscalability.com/blog/2013/11/25/how-to-make-an-infinitely-scalable-relational-database-manag.html

by jpmc • 13 years ago

154 89 13 years ago

highscalability.com

gopalv2• 13 years ago

GNU AFPL?

Clause 13 is a real pain to deal with when exposing this over the network.

I guess the developer wants to sell a license (like the mysql java client GPL'ing).

Can't blame him, he needs to get paid.

samspenc2• 13 years ago

MongoDB does this too. I personally think its not too bad - its free for whoever wants to use it, but if you want to modify and use it commercially, you do have to pay.

mtravis25• 13 years ago

Hi, gopalv. What samspenc said. My understanding of the AGPL is that only the modifications made to the source code itself of the covered project would need to be opened up (or have a commercial license). Meaning that merely using InfiniSQL won't require you to open source your app. MongoDB has the same license BTW, and lots of people use it without being forced to open their code. And, yes, I want to get paid somehow--but the AGPL won't stop anybody from using my work how they see fit. But if they modify it and distribute it, then they'll have to comply with the license (or contact me directly for an alternate arrangement).

gopalv2• 13 years ago

I fully understand what this means and I hope you do get calls about alternate licensing, but remember that people like me do not make these decisions.

I thankfully don't have to - this means I don't need to talk to lawyers about this.

Because AGPL took away the most important bit of unassailable ground I had to argue with when it came to deploying GPL - "Using this code implies no criteria we have to comply to, only if we distribute it".

Clause 12 and 13 - basically took that away from me completely.

Look, I'm not going to tell you what license to use.

But leave me enough room to complain that I have had trouble convincing people that we can use AGPL code in a critical function without obtaining a previous commercial license by paying the developer.

alanctgardner22• 13 years ago

I'm a little skeptical:

- a bunch of the novel components (the UPS aware persistence layer, for example) aren't actually built yet

- they're pushing for people to build businesses on it already. I would characterize it as "bleeding-edge with bits of glass glued on", so this doesn't seem entirely honest.

- there's mostly a lot of breathless talk about how great and fast and scalable it is, but no mention of CAP theorem. To boil down their feature set, it's an in-memory RDBMS using the Actor model.

mtravis25• 13 years ago

Hi, Alan. Yes, many things are not built yet. Nowhere am I pushing anybody to build their business on it yet, but I am looking for hackers and early adopters/alpha testers. I've gone through pains on every doc that I've created that this is early, alpha, needs lots of work--including the 2nd paragraph of the linked-to article: "InfiniSQL is still in early stages of development--it already has many capabilities, but many more are necessary for it to be useful in a production environment."

Regarding CAP, I'm not addressing multi-site availability at this stage--I want to get single site fully operational, redundant, and so on.

And, yes, to boil it down, it's an in-memory RDBMS using the Actor model.

The most important feature is that it performs transactions involving records on multiple nodes better than anything. This is the workload that keystores functionally cannot do, and which other distributed RDBMS' suffer under. It's also open source, has over 100 pages of technical docs, and is functional enough for people to pound on with some workloads--but not something to put into production yet.

alanctgardner22• 13 years ago

CAP theorem can apply to any clustered system, it doesn't have to be multi-site. What happens if 6 of your 12 machines die? What if they get cut off from the other 6?

edit: There's a bit of discussion further down about the SQL implementation. That's something I was very curious about as well. The projects linked below spend a lot of time working on supporting full ANSI SQL, and reducing latency by pushing down as many operations as possible. The Overview page doesn't appear to mention how filtering, aggregation, windowing, etc. work in your system.

Also, I noticed on your website that you compare InfiniSQL to Hadoop. How do you feel it compares to Impala (http://blog.cloudera.com/blog/2012/10/cloudera-impala-real-t...) and Shark (https://amplab.cs.berkeley.edu/projects/shark-making-apache-...)?

brianpgordon• 13 years ago

When I see a new distributed database, the first thing I want to know is "Is it AP or CP?"

If you haven't answered that question yourself, it's likely you have a partition-intolerant system, and that in real-life scenarios people will lose data.

eksith2• 13 years ago

Nowhere am I pushing anybody to build their business on it yet...

"In fact, InfiniSQL ought to be the database that companies start with--to avoid migration costs down the road."

This is far from looking for hackers and early adopters. I understand that you're enthusiastic about something you've created, but let's be reasonable for a moment. I'm more than happy to try this out, but starting my business on something that isn't proven yet and has a fair number of durability features yet to be implemented is a no, no.

Edit: My posts on this thread may be coming off as negative and that's not what I intended. I'm cautious of new technology that purports to deliver the world to me on a silver platter. That said, I'd be happy to throw everything I've got at it to see what shakes loose so you can get this to production quality sooner.

MichaelGG6• 13 years ago

In-memory distributed database? VoltDB is already way past 500Ktx/sec on a 12-node cluster.

On their site though, it says no sharding and that it can do these 500Ktx/sec even when each transaction involves data on multiple nodes. Does this performance degrade directly in relation to the number of nodes a tx needs to touch?

A simple, straightforward, wire-level description of how things work when coordinating and performing transactions across would be very useful. There's a lot of excited talk about actors, but nothing that really examines why this is faster, or any sort of technical analysis.

mtravis25• 13 years ago

Hi, Michael. Yes, VoltDB is very fast, but they self-admittedly do not perform well if transactions contain records spanning across multiple nodes. That is the key feature difference between InfiniSQL and VoltDB (along, of course, that their project is functionally much further along).

If you want more details about how things work when performing transactions, I think that the overview I created would be a good starting point. It probably doesn't have everything you'd ask for, but I hope that it answers some of your questions: http://www.infinisql.org/docs/overview/

And to answer your question about performance degradation pertaining to number of nodes each transaction touches, I have not done comprehensive benchmarks of InfiniSQL measuring that particular item. However, I do believe that as multi-node communication increases, throughput will tend to decrease--I expect that the degradation would be graceful, but further testing is required. The benchmark I've performed and referenced has 3 updates and a select in each transaction, all very likely to be on 3 different nodes.

I'd like to invite you to benchmark InfiniSQL in your own environment. I've included the scripts in the source distribution, as well as a guide on how I benchmarked, as well as details on the specific benchmarking I've done so far. All at http://www.infinisql.org

I'd be glad to assist in any way, give pointers, and so on, if there are tests that you'd like to do. I also plan to do further benchmarking over time, and I'll update the site's blog (and twitter, etc) as I do so.

Please communicate further with me if you're curious.

Thanks, Mark

jbellis3• 13 years ago

So basically, VoltDB acknowledges that cross-partition transactions are Hard and has put a lot of effort into minimizing them. (This is basically the entire point of the original HStore paper.)

InfiniSQL says don't worry, we'll just use 2PC. But not just yet, we're still working on the lock manager.

I look forward to your exegesis of how you plan to overcome the well-documented scaling problems with 2PC. Preferably after you have working code. :)

MichaelGG6• 13 years ago

Hey Mark. The overview seem to be much of the same. There's a lot of excited talk, which is fine, but should be limited to a leading paragraph. The fundamental issue is performance in face of transactions that need to do 2PC among multiple nodes (which also need to sync with the replicas).

I'm not much of an expert at all, but I like reading papers on databases. It seems to me that if you really did discover a breakthrough like this, you should be able to distill it to some basic algorithms and math. And a breakthrough of this scale would be quite notable.

If I'm reading correctly, there's no replica code even involved ATM. So 500Ktx/s really boils down to ~83Ktx/sec per node, on an in-memory database. Is it possible on modern hardware that this is just what to expect?

I am curious, and I'm not trying to be dismissive, but the copy sounds overly promising, without explaining how, even in theory, this will actually work. I'd suggest to explain that part first, then let the engineering come second.

yid3• 13 years ago

UPS systems will stay active for a few minutes, based on their capacity, and the manager process will gracefuly shut down each daemon and write data to disk storage. This will ensure durability--even against power failure or system crash--while still maintaining in memory performance.

How does a UPS ensure durability against system or program crashes, disk corruption in large clusters, and other failures that can affect a simple write()?

The real killer for database performance is synchronous transaction log writes. Even with the fastest underlying storage, this activity is the limiting factor for database write performance. InfiniSQL avoids this limiting factor while still retaining durability

How do you plan to implement this (since it appears it hasn't been implemented)? What is your fundamental insight about synchronous transaction logs that makes InifiSQL capable of being durable while (presumably) not having a synchronously written transaction log? If your answer is the UPS, please see my first question.

Edit: I don't see any mention of Paxos anywhere. Could you explain what you're using for consensus?

mtravis25• 13 years ago

Hi, yid. UPS protects against multiple simultaneous system crashes. Single system crash gets failed over, no problem. If both UPS systems detect their upstream PDU's as being out, then the InfiniSQL management protocol will initiate graceful shutdown, including persisting to disk. For write() issues, at least intially, I think that stuff in commodity hardware (such as ECC memory) is sufficient protection in most cases. Attaching a high end storage array, or using ZFS, also protects against low level disk problems. I don't see those problems as needing to be solved for a 1.0 relase, but am very much open to contributions that address those issues any time you want!

The fundamental insight about not needing transaction logs is pretty simple actually: if the power is guaranteed to either stay on, or to allow the system to quiesce gracefully, then the cluster will not suddenly crash. That's the motivator for transaction logs--to make sure that the data will still be there if the system suddenly crashes. Get rid of the need for transaction logs, get rid of the transaction logs.

Regarding consensus, I expect that there will be a quorum protocol in use amongst an odd number greater than 2 of manager processes, each with redundant network and power. But the specific protocol I haven't ironed out. If there's something I can grab off the shelf then it may be preferable to implementing from scratch, but I haven't gotten there yet.

This stuff hasn't been implemented yet, but the core around which it can be implemented, has been.

Do I sense a volunteer? ;-)

yid3• 13 years ago

I feel like you're banking a little too heavily on external measures for error protection/durability like UPSes and ECC memory, rather than embracing the inevitable fact that corruption and failures will occur. In short, I'd really need to see a white paper on why you're not reinventing the wheel before I'd use InifiSQL.

Kudos for engaging the community though; please do keep us posted as you progress.

MichaelGG6• 13 years ago

Well one example is that bug that caused a panic on a certain date (I think it may have been leap year related) - machines just die then. Only way to recover from that would be some neat reboot system that recovers the data from RAM. But, all systems have dataloss, so this problem affects any main-memory system.

You may get more volunteers by publishing a paper outlining the core concept. I clearly remember reading things like the H-Store paper, or the Dremel paper, and saying "damn, this makes sense and is really cool". Implementation details can be worked out and engineering approaches tried. But the underlying concept should be clear.

ams61102• 13 years ago

UPSs don't always work as expected.

brianberns• 13 years ago

An in-memory RDBMS hardly seems to be "infinitely scalable". How would this work with DBs in the terabyte size or larger?

glogla4• 13 years ago

Badly. But scaling in dataset size, and scaling in performance are not the same thing. Busy eshop might need no more than 5 GB of space (growing 100 MB per month or something) but require very high speed.

mtravis25• 13 years ago

Well, 2-way Cisco servers can hold 1TB RAM each.

It scales as long as throughput increases while new nodes are added. I've done benchmarking up to 12 nodes, and it continued to scale nearly linearly. (http://www.infinisql.org/blog). I'd like to push it further, but need $$$ for bigger benchmark environments.

MichaelGG6• 13 years ago

A terabyte of RAM is pretty cheap. Around $12K for the RAM. Last I quoted out a system for VoltDB, the total cost (complete servers with CPU, disk, RAM) came to ~$17/GB to $22/GB.

If you actually have transaction processing at this scale and need that performance, the RAM cost is not a major issue.

glogla4• 13 years ago

There was very interesting presentation by one professor. I'm not sure about what university, but he seemed to know his work.

He talked about how databse world is about to change. ACID is really expensive in terms of resources, and so are the more difficult things about relational schema (foreign keys, checks, etc). And architecture of classic RDBMSes is pretty wasteful -- they use on-disk format but cache it in memory.

He talked about how there are basically three new paths for DBMSes to follow. 1) Some drop the restrictions to become faster. This is the NoSql stuff, because you don't really need ACID for writing to Facebook wall.

This is called NoSql database.

2) OLAP, in data warehousing, the usual way to do things is that you load ridiculous amount of data into database, and then run analytical queries, that tend to heavily use aggregation and sometimes use just few dimmensions, while the DWH data tend to be pretty wide.

For this, column store makes perfect sense. It is not very quick on writes, but it can do very fast aggregation and selection of just few columns.

This is called Column store.

3) In OLTP, you need throughtput, but the question is, how big are your data, and how fast do they grow? Because RAM tends to get bigger exponentially, while how many customers you have will probably grow linearly or maybe fuster, but not much. So your data could fit into memory, now, or in future.

This allows you to make very fast database. All you need to do is to switch the architecture to memory-based, store data in memory format in memory and on disk. You don't read the disk, you just use it to store the data on shutdown.

This is called Main memory database.

No, that was the presentation. It was awesome, and if someone can find it, please give us a link! My search-fu was not strong enouhg.

...

What interests me is that we have NoSql databases for some time already, and we have at least one huge (are very expensive) column store: Teradata. But this seems to be first actual Main memory database.

My dream would be to switch Postgres to main memory or column store mode, but I guess that's not happening very soon :)

pge• 13 years ago

To add to your list, Vertica (HP) and Paraccel are columnar; TimesTen was a main-memory database bought a number of years ago by Oracle.

twoodfin• 13 years ago

That sounds very much like Michael Stonebraker's typical pitch these days.

JeffDClark• 13 years ago

Is this the talk that you are referring to? http://slideshot.epfl.ch/play/suri_stonebraker

glogla4• 13 years ago

Yes, that's the one. Thank you! I'm bookmarking it right now.

ezequiel-garzon• 13 years ago

If I may drool a little, you guys represent the heart of Hacker News. Insightful summary, mentioning that somewhere somebody gave such a talk. As I was reading the first comment I was silently cheering for "a librarian's follow-up", and there it was!

nl• 13 years ago

Note that Stonebraker makes some good points, but there are many ways to build scalability and Stonebraker is too fast to dismiss many.

In particular, his criticism of traditional databases seems based more on philosophy rather than evidence.

I'd advise reading both sides of the story:

http://lemire.me/blog/archives/2009/09/16/relational-databas...

http://lemire.me/blog/archives/2009/07/03/column-stores-and-...

http://architects.dzone.com/articles/stonebraker-talk-trigge...

http://gigaom.com/2011/07/11/amazons-werner-vogels-on-the-st...

http://dom.as/2011/07/08/stonebraker-trapped/

The date on some of those posts in interesting. 2009 is quite a while ago now, and I'd suggest that columnar datastores haven't exactly taken over. Some implementations have made some progress (eg Cassandra), but OTOH many non-traditional datastores have added traditional-database like features (eg, Facebook's SQL front end on their NoSQL system), and traditional databases have added NoSQL features too.

d4mi3n• 13 years ago

You mentioned OLTP. Erlang's Mnesia store comes to mind, but as far as I'm aware it's limited to a 4GB data set. I'm not sure if that qualifies as a main-memory db, but it might be similar.

mbesto• 13 years ago

But this seems to be first actual Main memory database.

Eh, not really...

This is exactly what SAP has been doing for several years via Hasso Plattner and the Potsdam Institute: https://epic.hpi.uni-potsdam.de/Home/HassoPlattner

If you've ever worked with large scale "enterprise" database warehouses, they tend to be slow and clunky. Back in 2006ish SAP took the whole Data Warehouse (well mainly just the data cubes) and chucked it into a columnar database (at the time it was called TREX, then became BW Accelerator) - http://en.wikipedia.org/wiki/TREX_search_engine

TREX exist way before 2006. SAP also bought a Korean company called P* (IIRC) which did non-columanr (traditional relational) and threw it into memory. SAP also had a produce called APO LiveCache - http://scn.sap.com/community/scm/apo/livecache - which lived around the same time.

This has now all evolved to a standard offering called SAP HANA - http://www.saphana.com/welcome - In it's second year of inception I believe SAP did roughly $360m in sales just on HANA alone.

Also, IIRC is InnoDB basically the open source version of exactly what you're talking about with "Postgres to main memory"?

edit- correction in TimesTen

army2• 13 years ago

InnoDB isn't anything like that - it's a transactional database engine that's been around since the 90's and has since become the standard storage engine for MySQL - it competes directly with Postgres' storage layer.

ams61102• 13 years ago

A few years ago I was tinkering with Haskell and looked at a framework call HAppS which kept all its state in memory. Doesn't look like the project has really been active lately.

donri• 13 years ago

HAppS is dead, long live Happstack!

What you're talking about was the HAppS-State component of the HAppS application server, a project which is in deed not active anymore. Happstack is the active fork of HAppS and had a "happstack-state" component for a while, but this was eventually rewritten from scratch and made independent of Happstack and is now known as acid-state [1]. It's even used for the new Hackage server that powers the Haskell package ecosystem.

[1] https://github.com/acid-state/acid-state

hatchoo• 13 years ago

And just to add to the list of c-store databases, there's also Sybase IQ. (I believe Sybase is now owned by SAP so it may have been rebranded)

flatfilefan2• 13 years ago

Teradata is not a column store afaik. Vertica would be a good example of such.

leandrod• 13 years ago

My dream would be to switch Postgres to main memory or column store mode, but I guess that's not happening very soon :)

If it can be done besides the traditional architecture, be it in a fork or without touching existing code; and if you can at least start the work, it could happen soon.

amalag• 13 years ago

This is what Clustrix (YC company) claims to do.

mtravis25• 13 years ago

Hi, amalag. Yes, Clustrix is very similar to InfiniSQL (not to mention having been around longer). I believe that InfiniSQL has vastly higher performance at least for the type of workloads that InfiniSQl is currently capable of. InfiniSQL is also open source.

I hope there's room for competition in this space still.

sergei2• 13 years ago

What do you base your performance claim vs Clustrix on?

jeremycole• 13 years ago

What's up with the weird coding standards? Include files named infinisql_*.h and #line statements... strange.

mtravis25• 13 years ago

Oh, the infinisql_*.h is because I deploy all header files as part of "make install", when what I really should do is boil it down to just the api header. The api is for stored procedure programming. Yes, I have it on backlog to fix. I give them all that name in case somebody installs to /usr/local (which you probably oughtn't) it's clear what application they all belong to. Yes, I could create a subdirectory, too. But the fix will be when I clean up api.cc to only have to pull in the one header instead of several of them.

#line statements because I get compiler messages from time to time putting things on the wrong line after having imported headers.

leif5• 13 years ago

The write bottleneck for traditional databases has never been the write-ahead log, with group commit and a battery-backed RAID controller you'll have a hard time saturating the disk with log writes. The bottleneck has always been random I/O induced by in-place updating indexes based on B-trees. You don't need to be in-memory if you use better data structures. TokuDB and TokuMX are proof of that.

mtravis25• 13 years ago

Hi, Leif. It's not hard to get to the throughput limits of a single log device, even on a fast array. I've done it on Sybase, WebSphere MQ, Oracle, MySQL, basically on enough platforms that I assume it to be the general case. The log writes don't saturate the array itself--but the log file has a limit to how many blocks can be appended--even on fast arrays. But imagine getting rid of the transaction log entirely--the entire code path. That will be faster even than a transaction log write to memory-backed filesystem.

But I agree that other write (and read) activity going on in the background and foreground, also limits performance--and in fact, I've seen the index write bottleneck that you describe in real life, more-so than simple transaction log writes. So, you're correct.

I've read about Toku, but I really doubt that it writes faster to disk than writing to memory. Are you really trying to say that?

I think it would be great for InfiniSQL to be adapted to disk-backed storage, in addition to memory. The horizontal scalability will also apply, making for a very large group of fast disk-backed nodes.

I think your input is good.

VladRussian23• 13 years ago

The log writes don't saturate the array itself--but the log file has a limit to how many blocks can be appended--even on fast arrays

yes, the issue usually isn't the transaction log append speed. Instead, it happens too frequently that the log is configured to be too small. A log file switch causes a flush of accumulated modified datablocks of tables and indexes [buffer cache flush in Oracle parlance] from RAM to disk. With small log file size, the flush happens too frequently for too small amounts of modified data - this is where GP mentioned random IO bites in the neck.

leif5• 13 years ago

I'm not talking about the speed of the array, rather a battery backed controller. With one of those, as long as you're under the sequential write bandwidth of the underlying array, it pretty much doesn't matter how much you fsync the log, so that bottleneck (commit frequency) goes away.

If you're planning to write data faster than disk bandwidth, then you have no hope of being durable and we're talking about problems too different to be worth comparing, and in that case I retract my comment.

I don't understand what distinction you're trying to make between the "array itself" and the "log file has a limit to how many blocks can be appended". Can you clarify what limit you're talking about?

eksith2• 13 years ago

Looking at the "About and Goals" section of their docs http://www.infinisql.org/docs/overview/#idp37033600

I can't seem to find the word "Reliable" or any variation thereof anywhere in there.

In fact, that word is no where to be found on the blog post or on the entire InfiniSQL page (not in the Overview, Guides, Reference or even FAQ). I find this quite remarkable since reliability is the true virtue of an RDBMS, not speed or even capacity. At least that's what PostgreSQL aims for and this being another RDBMS, and is also open source, I see it as InfiniSQL's only direct competitor.

It's nice that this is scalable, apparently, to ridiculous levels, but if I can't retrieve what I store in exactly the same shape as I stored it, then that's a bit of a buzz kill for me.

Can we have some assurance that this is the case?

There's a note on "Durability" and a shot at log file writing for transactions, and presumably InfiniSQL uses concurrency and replicas, to provide it. In the Data Storage section, it mentions that InfiniSQL is still an in-memory database for the most part http://www.infinisql.org/docs/overview/#idp37053600

What they're describing is a massively redundant, UPS backed, in-memory cache.

Am I wrong?

mtravis25• 13 years ago

Hi, eksmith. I talk a bit about plans for durability in that overview document.

I promise that I have every intention of making InfiniSQL a platform that does not lose data. I have a long career working in environments that demand 100% data integrity. If I de-emphasized it, it was not intentional.

PostgreSQL doesn't scale for OLTP workloads past a single node. There are a handful of products similar to InfiniSQL (google for the term NewSQL for a survey of them).

And yes, a redundant UPS-backed in-memory cache. I have some ideas on how to do regular disk backing as well (which I'm sure you've read).

And if a more traditional log-based storage layer is added, InfiniSQL will still scale nearly linearly across nodes horizontally. Multi-node scale and in-memory are not dependent on one another. Though I believe that redundant UPS systems managed by a quorum of administrative agents, and provide durability just like writing to disk.

Are you familiar with high end storage arrays, such as from HDS or EMC? They write to redundant memory, battery backed and managed by logic in the arrays. I'm just moving that type of design to protect the database application itself, up from the block layer.

And some people trust their datacenter power--they use pure in-memory databases without UPS already, or they do things like asynchronously write transaction log, which also sacrifices durability. For those groups, InfiniSQL ought to be just fine, without UPS systems.

flatfilefan2• 13 years ago

What is the difference to Teradata or Netezza except this is open source and lack the burden of universality yet?

mtravis25• 13 years ago

Those are analytics databases, also known as data warehouses. Optimized for batch reporting. InfiniSQL is geared for operational/transactional (OLTP) kinds of workloads.

How To Make An Infinitely Scalable RDBMS

Related Stories