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Databases · head to head

Apache Solr vs turbopuffer

Apache Solr logo

Apache Solr

Databases

Enterprise search platform built on Apache Lucene

From
Free
Rated
-
Full reviewWebsite
turbopuffer logo

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
-
Full reviewWebsite

The short version

  • Only Apache Solr has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Solr xML-heavy configuration and a developer experience that feels dated beside newer engines; 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: Apache Solr covers Lucene-based indexing, turbopuffer covers Object storage architecture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Solr and turbopuffer actually diverge.

Attributes where Apache Solr and turbopuffer differ
AttributeApache Solrturbopuffer
Starting priceFree$16/month
Pricing modelOpen source, no licence feesubscription
Free tierYesNo
PlatformsLinux, Docker, Kubernetes, Self-hostedWeb

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 Apache Solr

  • Lucene-based indexing
  • Faceted search
  • SolrCloud
  • Schema control

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.

Apache Solr

  • Library, archive and catalogue search where faceting is centralnot turbopuffer
  • Long-lived enterprise deployments valuing stability over noveltynot turbopuffer
  • Search requiring precise, explicitly configured relevance tuningnot turbopuffer

turbopuffer

  • A product with one search index per customer and thousands of customers, most of whose data is idle on any given daynot Apache Solr
  • Very large corpora where holding every vector in memory is the dominant cost and occasional cold-query latency is acceptablenot Apache Solr
  • Hybrid retrieval combining BM25 and vector search where running and synchronising two separate systems is the problem being solvednot Apache Solr
  • Retrieval for agent and assistant products where indexes are created and destroyed frequently and per-index overhead must be near zeronot Apache Solr

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Apache Solr

  • XML-heavy configuration and a developer experience that feels dated beside newer engines
  • SolrCloud depends on ZooKeeper, adding a component Elasticsearch removed years ago
  • Smaller mindshare now, so newer tutorials, hiring and integrations favour Elasticsearch
  • Considerably heavier than a purpose-built application search engine

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

Apache Solr

Free
  • Apache SolrFree
    • Full functionality
    • No usage limits
    • Community support

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 Apache Solr if

  • You need lucene-based indexing.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want faceted search.
Apache Solr review

Choose turbopuffer if

  • You need object storage architecture.
  • You also want namespaces.
turbopuffer review

Questions people ask

Is Apache Solr or turbopuffer better?
Neither clearly leads. Apache Solr 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, Apache Solr or turbopuffer?
Apache Solr has a free tier; the other does not. Paid plans start at Free for Apache Solr and $16/month for turbopuffer.
Does Apache Solr or turbopuffer run on more platforms?
Apache Solr runs on Linux, Docker, Kubernetes, Self-hosted. turbopuffer runs on Web.
Can I use Apache Solr for free?
Yes. Apache Solr has a free tier, so you can try it without paying. turbopuffer starts at $16/month.
What is Apache Solr best used for?
Apache Solr is most often used for library, archive and catalogue search where faceting is central, long-lived enterprise deployments valuing stability over novelty, search requiring precise, explicitly configured relevance tuning. Of those, library, archive and catalogue search where faceting is central and long-lived enterprise deployments valuing stability over novelty are not what turbopuffer is typically brought in for.
What can Apache Solr do that turbopuffer cannot?
Apache Solr covers Lucene-based indexing, Faceted search, SolrCloud, Schema control. turbopuffer covers Object storage architecture, Namespaces, Vector search, Full-text search.

Answered from the vendors’ own pages

Apache Solr: Is Apache Solr free?

Yes, open source under the Apache Software Foundation.

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.

Apache Solr: Solr or Elasticsearch?

Both are built on Lucene. Elasticsearch has the larger ecosystem and a friendlier API; Solr is very mature and strong on faceted search, and remains common in library and catalogue systems.

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.

Apache Solr: Is Solr still maintained?

Yes, actively, as a top-level Apache project.

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.

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.

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