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Chroma vs LanceDB

Chroma

trychroma.com

LanceDB

lancedb.com

Side by side

FigureChromaLanceDB
Price from$250/moFree
Free planYesYes
Free trialYes—
Open sourceYes—
WebYes—
WindowsYes—
macOSYes—
LinuxYesYes
iOSYes—
AndroidYes—
APIYesYes
Self-hostedYesYes
Plans published42
Spec score · Ai Databases9.4 (#1)7.8 (#21)
Spec score · Embedded Databases9.4 (#1)7.8 (#16)
Spec score · Vector Databases9.4 (#1)7.8 (#15)
Spec score · Search Databases9.3 (#2)7.7 (#21)
Spec score · Database Software8.7 (#20)7.3 (#72)
SearchChroma supports dense, sparse, and hybrid vector search, full-text and regex search, and metadata filtering.It supports vector or semantic search, full-text search, and hybrid search with SQL filters.

Plans

Chroma

  • StarterFree
  • Team$250 a month
  • StarterFree
  • EnterprisePriced on request

Chroma pricing →

LanceDB

  • LanceDB OSSFree
  • LanceDB EnterprisePriced on request

LanceDB pricing →

In their own words

Chroma

Chroma is open-source infrastructure for storing embeddings and metadata, then searching and retrieving information across text, images, and other modalities. Search options include dense, sparse, and hybrid vector search, plus full-text and regex search and metadata filtering. It can run locally through pip, npm, or Docker, on Chroma Cloud, or in a customer’s own VPC. The maker says its Apache 2.0-licensed codebase powers both the open-source database and Chroma Cloud. Documented integrations include embedding providers such as OpenAI, Cohere, Google Gemini, Hugging Face, Jina AI, and Ollama, and frameworks such as LangChain, LlamaIndex, Haystack, Streamlit, and DeepEval. Cloud security features include encryption in transit and at rest, SSO, role-based access control, and employee MFA; Chroma Cloud has completed a SOC 2 Type II examination. Starter is free, with 10 databases and 10 team members. Team is $250 a month plus usage and includes $100 credits, 100 databases, and 30 team members.

Visit trychroma.com

LanceDB

LanceDB is an open-source, AI-native multimodal lakehouse for developing training datasets. It brings raw bytes, enriched features, metadata, and embeddings into searchable tables. Search supports vector or semantic queries, full-text search, and hybrid queries with SQL filters. Dataset curation includes deduplication and identifying edge cases for labeling. Users can write local Python UDFs and run declarative feature pipelines at petabyte scale, according to the product page. Writes are automatically versioned, allowing branches, rollbacks, and experiment tags without duplicating data. The Enterprise suite covers Search, Exploratory Data Analysis, Feature Engineering, and Training, with platform-level index and table limits and safety checks for operations such as merge_insert. Lance Namespace names Apache Hive Metastore, AWS Glue Catalog, and Apache Spark integrations. Workloads can be distributed through Ray and KubeRay on on-premises or cloud clusters. LanceDB OSS is free for local or storage-path connections.

Visit lancedb.com