Databases · head to head
Timeplus vs turbopuffer

Timeplus
Databases
Streaming SQL engine built on ClickHouse internals, shipping as one small binary
- From
- Free
- Rated
- -

turbopuffer
Databases
Closed-source vector and full-text search service built directly on object storage, with cold queries measured in seconds rather than milliseconds.
- From
- $16/month
- Rated
- -
The short version
- Only Timeplus has a free tier, so it costs nothing to try first.
- Each has a real cost: Timeplus proton, the free version, is single-node by design, so any requirement for high availability or horizontal scale forces the commercial licence; the open source edition is a trial in practical terms.; turbopuffer a cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
- They diverge on capability: Timeplus covers Streaming SQL, turbopuffer covers Object storage architecture.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Timeplus and turbopuffer actually diverge.
| Attribute | Timeplus | turbopuffer |
|---|---|---|
| Starting price | Free | $16/month |
| Pricing model | Per month for cloud, quoted for self-hosted | subscription |
| Free tier | Yes | No |
| Platforms | Linux, macOS, Docker, Kubernetes, Web | Web |
Identical on both: user rating (Not yet rated), category (Databases).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Timeplus
- Streaming SQL
- Unified streaming and historical
- ClickHouse-based engine
- Single binary deployment
- External streams
- Materialised views
Only in turbopuffer
- Object storage architecture
- Namespaces
- Vector search
- Full-text search
- Attribute filtering
- Documented limits
- Configurable consistency
- Durable writes
What people use each for
The jobs each tool is most often brought in to do.
Timeplus
- Real-time alerting on Kafka topics where standing up a Flink cluster is more work than the use case justifiesnot turbopuffer
- Fraud or anomaly detection that must join a live event stream against recent history in one querynot turbopuffer
- Streaming ETL from Kafka or MySQL change data capture into ClickHouse without writing Javanot turbopuffer
- A small data team that needs continuous aggregation but has no platform engineers to operate JVM infrastructurenot turbopuffer
turbopuffer
- A product with one search index per customer and thousands of customers, most of whose data is idle on any given daynot Timeplus
- Very large corpora where holding every vector in memory is the dominant cost and occasional cold-query latency is acceptablenot Timeplus
- Hybrid retrieval combining BM25 and vector search where running and synchronising two separate systems is the problem being solvednot Timeplus
- Retrieval for agent and assistant products where indexes are created and destroyed frequently and per-index overhead must be near zeronot Timeplus
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Timeplus
- Proton, the free version, is single-node by design, so any requirement for high availability or horizontal scale forces the commercial licence; the open source edition is a trial in practical terms.
- It is a young project against Apache Flink’s decade of production history, so the hiring pool, the connector library and the body of known failure modes are all much smaller.
- Inheriting ClickHouse internals also inherits ClickHouse constraints: memory-hungry queries, awkward updates and a SQL dialect that is not portable to other engines.
- Exactly-once semantics and state recovery guarantees are less battle-tested than Flink checkpointing, which matters if the pipeline moves money.
- Cloud pricing is by provisioned instance size rather than usage, so a bursty workload pays for peak capacity around the clock or has to be resized by hand.
turbopuffer
- A cold namespace pays object storage latency on the first query, with a documented p90 around 1,214 ms on a million documents, so any interactive search box needs the data kept warm or the user waits about a second.
- Queries are eventually consistent by default, and after roughly 128 MiB of outstanding writes new data is invisible until indexed, which the vendor puts at tens of seconds for small namespaces and tens of minutes for large ones, so a bulk re-index is not immediately queryable.
- It is closed source with no community edition, so single-tenant or bring-your-own-cloud deployment is a commercial negotiation rather than a deployment choice, and there is no path to running it yourself if the relationship ends.
- Per-namespace ceilings, roughly 10,000 writes per second, 32 MB/s and 500 million documents per shard, mean a single enormous index has to be sharded across namespaces by your application rather than by the service.
- It is a search engine, not a database: there are no joins, no cross-document transactions and no SQL, so it sits beside a primary datastore and keeping the two in step is work that belongs to you.
Pricing, plan by plan
Timeplus
Free- Timeplus ProtonFree
- Apache 2.0 licence
- Single node only
- Full streaming SQL engine
- Timeplus Cloud$199/month
- One to thirty-two CPUs
- 4 GB to 128 GB memory
- From 250 GB SSD storage
- Self-hosted or BYOC$undefined/year
- Multi-node clustering
- Kubernetes or bare metal
- Customisable compute and storage
turbopuffer
$16/month- Launch$16/month
- All database features
- Multi-tenancy deployment
- SOC2 & GDPR-ready DPA
- Scale$256/month
- Everything in Launch
- HIPAA-ready BAA
- Single Sign-On (SSO)
- Enterprise$4096/month
- Everything in Scale
- Single-tenancy & BYOC deployment options
- Private networking
Which should you pick?
Choose Timeplus if
- You need streaming sql.
- You want to start without paying.
- You work on Linux, macOS, Docker, Kubernetes, Web.
- You also want unified streaming and historical.
Choose turbopuffer if
- You need object storage architecture.
- You also want namespaces.
Questions people ask
- Is Timeplus or turbopuffer better?
- Neither clearly leads. Timeplus starts at Free and turbopuffer at $16/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Timeplus or turbopuffer?
- Timeplus has a free tier; the other does not. Paid plans start at Free for Timeplus and $16/month for turbopuffer.
- Does Timeplus or turbopuffer run on more platforms?
- Timeplus runs on Linux, macOS, Docker, Kubernetes, Web. turbopuffer runs on Web.
- Can I use Timeplus for free?
- Yes. Timeplus has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
- What is Timeplus best used for?
- Timeplus is most often used for real-time alerting on kafka topics where standing up a flink cluster is more work than the use case justifies, fraud or anomaly detection that must join a live event stream against recent history in one query, streaming etl from kafka or mysql change data capture into clickhouse without writing java, a small data team that needs continuous aggregation but has no platform engineers to operate jvm infrastructure. Of those, real-time alerting on kafka topics where standing up a flink cluster is more work than the use case justifies and fraud or anomaly detection that must join a live event stream against recent history in one query are not what turbopuffer is typically brought in for.
- What can Timeplus do that turbopuffer cannot?
- Timeplus covers Streaming SQL, Unified streaming and historical, ClickHouse-based engine, Single binary deployment. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.
Answered from the vendors’ own pages
Timeplus: Is Timeplus open source?
The core engine, Timeplus Proton, is Apache 2.0. Timeplus Enterprise and Cloud are commercial.
turbopuffer: Can I self-host turbopuffer?
There is no open source or community edition. Single-tenant and bring-your-own-cloud deployments exist as commercial arrangements, but there is no way to run it independently of the vendor.
Timeplus: What is the difference from Flink?
Timeplus is one binary with SQL as the only interface; Flink is a JVM cluster with a Java and SQL API and far more operational surface.
turbopuffer: How fast is it really?
Warm queries perform comparably to in-memory search engines. Cold queries, where data is not cached, have a documented p90 around 1,214 ms on a million documents. Write p90 is around 248 ms for a 512 KB upsert because writes go straight to object storage.
Timeplus: Can Proton run in production?
It can, but it is single-node only, so there is no high availability without the commercial edition.
turbopuffer: Is it consistent?
Eventually consistent by default, with the vendor reporting that over 99.8% of queries return consistent data. Strong consistency can be requested per query at a latency cost. Large write bursts have a longer visibility delay while indexing catches up.
Timeplus: How much is the cloud?
From 199 US dollars a month, sized by CPU and memory, with a fourteen day trial.
turbopuffer: What is it best at?
Large numbers of namespaces where most are idle. The architecture makes cold data cheap to keep, which is exactly the shape of a multi-tenant product with a long tail of inactive customers.
turbopuffer: What are the hard limits?
Up to 128 billion documents and 256 TB per namespace, 500 million documents per shard, 64 MiB per document, 10,752 dense vector dimensions, roughly 10,000 writes per second per namespace and a maximum result set of 10,000.
Related pages
More on turbopuffer
Other head to heads
- Timeplus vs Apache Flink
- Timeplus vs ClickHouse
- Timeplus vs Materialize
- Timeplus vs Redpanda
- Timeplus vs NATS
- Timeplus vs DuckDB
- Timeplus vs Estuary
- Timeplus vs RisingWave
- Timeplus vs Meilisearch
- Timeplus vs Neo4j
- Timeplus vs OpenSearch
- Timeplus vs Qdrant
- Timeplus vs SingleStore
- Timeplus vs TiDB
- Timeplus vs Tinybird
- Timeplus vs Apache Kafka
- Timeplus vs Apache Pulsar
- Timeplus vs Apache Druid
- Timeplus vs PostgreSQL
- Timeplus vs Airtable
- Timeplus vs Cockroach Labs
- Timeplus vs Amazon Aurora
- Timeplus vs Chroma
- Timeplus vs BigQuery
- Timeplus vs Dremio
- Timeplus vs Typesense
- Timeplus vs Dragonfly
- Timeplus vs LanceDB
- Timeplus vs Readyset
- Timeplus vs Valkey
- Timeplus vs Apache Doris
- Timeplus vs ArangoDB
- Timeplus vs Canary Labs
- Timeplus vs Apache Solr
- turbopuffer vs Apache Flink
- turbopuffer vs ClickHouse
- turbopuffer vs Materialize
- turbopuffer vs Redpanda
- turbopuffer vs NATS
- turbopuffer vs DuckDB
- turbopuffer vs Estuary
- turbopuffer vs RisingWave
- turbopuffer vs Meilisearch
- turbopuffer vs Neo4j
- turbopuffer vs OpenSearch
- turbopuffer vs Qdrant
- turbopuffer vs SingleStore
- turbopuffer vs TiDB
- turbopuffer vs Tinybird
- turbopuffer vs Apache Kafka
- turbopuffer vs Apache Pulsar
- turbopuffer vs Apache Druid
- turbopuffer vs PostgreSQL
- turbopuffer vs Airtable
- turbopuffer vs Cockroach Labs
- turbopuffer vs Amazon Aurora
- turbopuffer vs Chroma
- turbopuffer vs BigQuery
- turbopuffer vs Dremio
- turbopuffer vs Typesense
- turbopuffer vs Dragonfly
- turbopuffer vs LanceDB
- turbopuffer vs Readyset
- turbopuffer vs Valkey
- turbopuffer vs Apache Doris
- turbopuffer vs ArangoDB
- turbopuffer vs Canary Labs
- turbopuffer vs Apache Solr
