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Why ekoDB
One database instead of a stack of services
Most teams stitch together a document store, a cache, a search engine, a vector database, and an auth layer, then spend their time keeping all of them in sync. ekoDB ships every one of those as native capabilities in a single Rust binary.
The result is less infrastructure to operate, lower latency because the data never leaves the process, and a feature set that is built in rather than bolted on. The benchmarks below put that against Redis, MongoDB, and Postgres.
What is ekoDB?
The next-generation application database - ultra-fast, schema-flexible, real-time capable, and AI Native.
Yesterday'sdatabasescan'tkeepupwiththeperformanceandfeaturedemandsoftoday'sapplications,butekoDBcan.BuildwithekoDB,andhavedocumentstorage,key-valueoperations,full-textsearch,vectorsearch,andmore,allinonepackage.
But is ekoDB fast?
Unrivaled performance capabilities
Powered by Rust, ekoDB has best-in-class performance across a wide variety of workloads. ekoDB is capable of lightning-fast sub-ms processing across all CRUD operations and significantly outperformed some of the world's most widely-used application databases in industry-standard performance testing. Even with its robust native feature set, ekoDB is one of the fastest and most efficient databases in the world. Read more about ekoDB's remarkable performance here.
How does ekoDB compare?
Outperforming the industry
In industry-standard YCSB performance benchmarking, ekoDB outperformed across every workload.*
*1M records, 64 threads, all databases configured to durable write modes
Composite score across all YCSB workloads (A, B, C, D, F) weighted by throughput (30%), latency (25%), CPU efficiency (25%), and cross-workload consistency (20%). Scores are relative — the best performer in each category receives full marks.
Documents / JSON / Row
Durable mode — all databases with matching fsync settings. ekoDB scores include full auth, encryption, search indexing, and real-time subscription overhead on every operation.
Key-Value
Cache mode — no persistence, pure throughput. ekoDB outperforms Redis (1.4x throughput, 30% lower latency) while carrying JWT auth, AES-GCM encryption, and search indexing that Redis does not provide.
Built-in, not bolted on
Features that require extensions or separate services elsewhere come native with ekoDB.
| Feature | ekoDB | PostgreSQL | MongoDB | MySQL | Redis |
|---|---|---|---|---|---|
| Built-in AuthApplication-level JWT tokens and API key authentication | JWT + API keys | Roles only | SCRAM only | Roles only | ACL only |
| Per-op EncryptionEvery read and write is encrypted at the operation level | AES-GCM | pgcrypto ext | CSFLE client-side | TDE / app-level | TLS in-transit only |
| Real-time SubsLive data streaming via WebSocket subscriptions | WebSocket | LISTEN/NOTIFY | Change Streams | needs external | Pub/Sub |
| Cross-DB SyncSync data across different database engines in real time | Ripple — Pg, Mongo, Redis | same-DB only | same-DB only | same-DB only | same-DB only |
| Key-Value StoreNative key-value operations alongside documents | Built-in | hstore ext | single-field docs | table workaround | Built-in |
| Document QueriesRich queries on flexible JSON documents | Built-in | JSONB | Built-in | JSON columns | RedisJSON module |
| Tunable DurabilityChoose durability vs speed globally or per operation | Global + per-op | synchronous_commit | Write concern | innodb_flush | appendfsync |
| Full-Text SearchSearch across text fields with ranking and stemming | Built-in | tsvector | Atlas Search | FULLTEXT index | RediSearch module |
| Vector SearchSimilarity search on embeddings for RAG and AI | Built-in | pgvector ext | Atlas only | needs Pinecone | RediSearch module |
| FunctionsRun logic on the server, co-located with your data | Server-side | PL/pgSQL | Atlas only | Stored procs | Lua scripts |
| SWR CachingStale-while-revalidate responses built into the server | Built-in | app-level only | app-level only | app-level only | manual TTL |
| AI ChatQuery your data in natural language with built-in RAG | Native RAG | needs external | Atlas only | needs external | needs external |
All of that in a single, tiny binary
Every feature above ships in one ~50 MB binary — no extensions, no separate processes, no assembly required.
What that looks like in practice
Fewer systems, less glue, lower latency
One system to run
Document storage, key-value operations, full-text search, vector search, real-time subscriptions, authentication, and per-operation encryption all live in the same database, so there are fewer moving parts to deploy, monitor, and reason about.
Lower latency by design
Because compute sits next to the data, queries and search avoid the extra network hops that a separate cache or search service would add on every request.
Built in, not bolted on
Capabilities that need extensions or extra services elsewhere ship natively in one binary that stays straightforward to deploy and operate as you scale.
Frequently asked questions
Is ekoDB a document, key-value, or vector database?
All of them. ekoDB is multi-model, with document storage, key-value operations, full-text search, and vector search in one engine.
Does it support transactions?
Yes. ekoDB provides ACID transactions with tunable durability, so you can trade latency for stronger guarantees per operation.
How does it compare to Redis, MongoDB, and Postgres?
In industry-standard YCSB benchmarking ekoDB outperformed across workloads, including faster reads and writes than MongoDB and Postgres, and higher throughput than Redis while also providing auth, encryption, and search.
Is ekoDB managed or self-hosted?
ekoDB is a managed cloud database. You deploy an instance per region and scale each deployment by machine tier.
Can it sync with databases I already run?
Yes. Ripple keeps data in sync across engines, including Postgres, MongoDB, and Redis.