HN user
VoltDB does support cross-partition transactions. They're not as fast as single-partition transactions, of course, because you're doing them over a network. But distributed transactions have been a supported feature since 1.0.
Fair question. We had some reservations about using EC2 for the reasons you mention. But we wanted to avoid any perceptions that we'd somehow cooked the books, so decided to run the tests on "neutral" gear.
If you look at the report details, you'll see some of the lumpiness your question suggests, particularly related to the network. The Node instances were beginning to starve when database server CPU utilization was still pretty low.
We would certainly have gotten better numbers if we ran these benchmarks on bare metal or a closely-tended cloud infrastructure. But we're a pretty low-BS group, so we'll stand behind what EC2 gave us.
As an in-memory RDBMS, VoltDB competes directly against products like Oracle TimesTen and IBM's SolidDB. Comparatively, VoltDB's architecture is designed specifically to scale out on clusters of commodity servers (TimesTem and SolidDB are single-node datastores), giving Volt access to larger amounts of inexpensive main memory.
VoltDB also competes indirectly with NoSQL products like Cassandra, which achieve performance and scale primarily by sacrificing SQL and ACID transactions (Volt preserves both).
As an in-memory database, VoltDB offers durability through command logging and disaster recovery via a recently-introduced feature called database (WAN) replication.
Hope this helps.
A few answers:
Yes, the tests were run without an ORM. Although VoltDB is accessible via JDBC, best throughput is achieved with parameterized SQL embedded in Java stored procedures. That's how the Node.js benchmark app (Voter) was implemented.
Node+Volt will be much faster than Node+Postgres or Node+MySQL for many OLTP-style workloads. So it's a great fit for apps like financial trading, digital advertising, online gaming and network monitoring - each of which requires super-high throughput writes (at single ms latencies) and fast, simple analytics. Node+Postgres or Node+MySQL would be a better fit for general purpose database workloads (e.g., with large-grained reporting).
In-memory means that Volt stores all data in main memory. Durability is achieved through the use of a highly innovative command log, which logs all transaction invocations to persistent storage. You can tune this feature to log synchronously (100% guaranteed durability at reduced transaction latency) or asynchronously (slightly more "lossy", but less of a latency impact). VoltDB also recently released a full database replication feature that supports WAN replication for disaster recovery.
I hope these responses are in some way helpful.