Congrats to the SurrealDB team! Shipping 3.0 is a serious milestone.
This is also a broader validation moment for the multi-model database space. In a market historically dominated by specialized, single-purpose systems (a separate DB for graphs, another for documents, another for search), it's meaningful that multiple independent projects — SurrealDB, ArcadeDB, and others — are converging on the same thesis: one database, many models. That kind of convergence signals the idea has real legs, not just as an engineering curiosity but as something the market is starting to demand.
If you're evaluating options in this space, worth also looking at ArcadeDB (https://arcadedb.com, Apache 2.0). It covers the same models — graph, document, key/value, time-series, full-text search, vector embeddings — but differs in a few practical ways:
- Query language: ArcadeDB speaks SQL, Cypher (OpenCypher-compliant with TCK testing), Gremlin, GraphQL, and MongoDB QL out of the box, so existing tooling tends to work without migration. The 26.2.1 release also added the Neo4j Bolt wire protocol, so standard Neo4j drivers connect directly.
- TimeSeries model is coming next week already compatible with the time series landscape, highly optimized
- License: Apache 2.0 with an explicit commitment to never change it. SurrealDB 3.0 ships under BSL 1.1, which converts to Apache 2.0 in 2030
- Runtime: Java 21, embeddable as a library or client-server, runs on Linux/macOS/Windows (x86_64 and ARM64).
Not saying one is better for all use cases — both are interesting takes on the multi-model problem. If BSL or SurrealQL lock-in are considerations for your team, ArcadeDB is in the same conversation.
Disclosure: I'm the founder of ArcadeDB and of OrientDB (now part of SAP - one of the DBMS SurrealDB was inspired by)
100% agree. Nobody is really interested on having ArangoDB on the cloud as a service. I guess >99% of the users are not paying and the company is running out of money (sales guys cost a lot!). I think this is a suicide for the product. Clients will remain, also because the switch is expensive. Their proprietary AQL is not easy to convert into SQL, Cypher or Gremlin....
It's hard to make OSS sustainable without millions of $ and VCs trying to turn that OSS tech in a huge business. With OrientDB we got lucky, not it's the past... Now I'm experimenting with a different approach of redistributing GitHub Sponsorships to the developers that actively work to the project:
After almost 18 months it's still far from being sustainable. Pure OSS is one of the hardest field to make some money because of the average developer: they just take without giving anything back in terms of work (contributing) or money.
What about https://arcadedb.com ? Open Source, Apache 2, Free for any usage. It supports SQL but also Cypher and Gremlin (and something of MongoDB and Redis query languages)
I agree that a pure ODBMS makes no much sense today, but OrientDB is a Multi-Model where the Object Model is one of the supported models. You can mix objects, graphs, schema-less documents and much more + using SQL as the query language. Boom!
Most of the Neo4j users don't use the TinkerPop, otherwise, it would be a drop-in replacement. If you're using Neo4j Cypher, you should use the SQL MATCH in OrientDB (very similar). Take a look at this page for the migration: https://dzone.com/articles/introducing-the-neo4j-to-orientdb....
For IBM Graph (that is Titan under the hood) you should install the TinkerPop plugin in Neo4j, export it as GraphML and then import it into IBM Graph. The query must be completely rewritten. In Gremlin 3 there is a minimal pattern matching, maybe you could try using that.
Nice reading and Kudos to the entire RethinkDB team for what they have done, especially the evangelization of the Reactive Model in the database. This inspired other vendors like OrientDB to do the same.
Running a company where a large part of the users is developers is very hard. The secret sauce is providing a good product and create a business where some of the users would pay to have something more, like support and/or an Enterprise edition.
The truth is, AFAIK, no NoSQL company backed by VC is still profitable today. Not even MongoDB that has got more than $300M and is able to collect just $60M/year by spending much more to be up & running.
> The secret sauce is providing a good product and create a business where some of the users would pay to have something more, like support and/or an Enterprise edition.
I was wondering about this, as it's not explicit in the article: What is the business model that makes money for Docker and MongoDB? From MongoDB's website I gather they have some "Enterprise" things, but they want me to give them my personal data just to access a "datasheet" describing this. Docker's "Enterprise" offering seems to be a mix of support and hosting.
So is that it? Support, hosting, and donations from Big Business?
The article also says: "Thousands of people used RethinkDB, often in business contexts, but most were willing to pay less for the lifetime of usage than the price of a single Starbucks coffee", but I don't understand what those users would have payed for. What was the product being sold? All I can gather from the article is some cloudy hosty database-as-a-service thing that might have made money but never shipped.
Support. Notwithstanding more widely accepted benefits of support like a direct line to the product's experts and in some cases, developers, big orgs are political tinderboxes and you're always one bad downtime away from an internal catastrophe, let alone an outage that affects customers. It's therefore often politically wise for decision-makers to purchase support even in cases where the risk analysis might show that internal talent resolve or work around most issues.
This is a variation of the "no one ever got fired for IBM" trope, and is in fact a big moneymaker for the likes of IBM, Oracle, Microsoft, and the like, even in situations where the standard notions of vendor lock-in may not even apply.
This is also a broader validation moment for the multi-model database space. In a market historically dominated by specialized, single-purpose systems (a separate DB for graphs, another for documents, another for search), it's meaningful that multiple independent projects — SurrealDB, ArcadeDB, and others — are converging on the same thesis: one database, many models. That kind of convergence signals the idea has real legs, not just as an engineering curiosity but as something the market is starting to demand.
If you're evaluating options in this space, worth also looking at ArcadeDB (https://arcadedb.com, Apache 2.0). It covers the same models — graph, document, key/value, time-series, full-text search, vector embeddings — but differs in a few practical ways:
- Query language: ArcadeDB speaks SQL, Cypher (OpenCypher-compliant with TCK testing), Gremlin, GraphQL, and MongoDB QL out of the box, so existing tooling tends to work without migration. The 26.2.1 release also added the Neo4j Bolt wire protocol, so standard Neo4j drivers connect directly.
- TimeSeries model is coming next week already compatible with the time series landscape, highly optimized
- License: Apache 2.0 with an explicit commitment to never change it. SurrealDB 3.0 ships under BSL 1.1, which converts to Apache 2.0 in 2030
- Runtime: Java 21, embeddable as a library or client-server, runs on Linux/macOS/Windows (x86_64 and ARM64).
Not saying one is better for all use cases — both are interesting takes on the multi-model problem. If BSL or SurrealQL lock-in are considerations for your team, ArcadeDB is in the same conversation.
Disclosure: I'm the founder of ArcadeDB and of OrientDB (now part of SAP - one of the DBMS SurrealDB was inspired by)
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