Actian Zen

Actian Zen is an embedded database for data management from edge environments to the cloud. Its lightweight engine brings together relational data, vector search, semantic queries, and connectivity for AI agents. Native vector search supports up to 1 million vectors, and hybrid queries combine relational filters with semantic similarity. Zen offers SQL and NoSQL access, including ODBC and JDBC for SQL and Btrieve and Btrieve 2 APIs for NoSQL. Local processing supports semantic search, vector queries, and AI-agent workflows offline, including in air-gapped environments. The product includes a native MCP server through which AI agents such as ChatGPT, Claude, and Gemini can query local data. Zen Enterprise is intended for embedded, on-premises, and cloud applications, including branch and remote field settings; the product page describes it for thousands of concurrent users, while Zen Edge supports over 100. Mobile editions support Android and iOS and list AES 256-bit encryption for data at rest. A 30-day trial is available, and paid pricing starts at $417/mo (annual).

Actian Zen combines relational database access with vector search and offline AI-agent workflows. Its trial offers a way to evaluate the product, while paid pricing starts at $417/mo (annual).

Zen suits developers and organizations building embedded or distributed applications that need local data processing and database access. Its mobile editions may suit projects targeting Android or iOS.

Overview

Actian Zen is an embedded database for applications that need relational and vector data close to where they operate, from mobile devices and remote sites to cloud deployments. It is best suited to teams building data-intensive software that needs SQL and NoSQL access, offline operation, or links to AI agents. Its breadth is compelling, but custom product pricing and a paid entry point make it a more considered choice than a free vector database.

Key features

Zen combines relational data with native vector search, supporting up to 1 million vectors and hybrid queries that apply relational filters alongside semantic similarity. That combination can suit applications where semantic results need to respect structured records or metadata, rather than relying on vector similarity alone. HNSW and flat index types and metadata filtering add options for organizing that search.

SQL access uses ODBC and JDBC; NoSQL access is available through Btrieve and Btrieve 2 APIs. Python, JavaScript, and C++ SDK languages give development teams additional integration paths. The product also includes a native MCP server that lets AI agents such as ChatGPT, Claude, and Gemini query local data. These capabilities are especially relevant when an application needs agent workflows without sending local data to a remote service: Zen describes semantic search, vector queries, and agent workflows operating offline, including in air-gapped environments.

Deployment can be embedded, on premises, or in the cloud. Enterprise platform support includes Windows, Linux, and macOS, Intel and ARM, plus VMware, Hyper-V, and Docker. Zen Mobile targets Android and iOS and lists AES 256-bit encryption for data at rest. Zen Edge supports over 100 concurrent users, while Enterprise is designed for thousands, putting the product within reach of both smaller edge deployments and larger installations.

Actian also offers related operational tools: DataExchange synchronizes Zen databases in real time and uses built-in 256-bit encryption; Audit Master records database access and changes; and Backup Agent supports continuous backups and an embeddable API. These are useful complements for deployments with replication, audit, or backup needs, though they are separate products rather than reasons to assume those capabilities are all built into Zen.

Pricing

Actian describes its pricing model as freemium, but there is no free plan. The paid entry point is $417/mo (annual), so the stated starting price commits buyers to an annual term and may be a substantial hurdle for a small project or early evaluation. The Actian Zen plan itself has custom pricing; buyers need to contact Actian or book a demo for product information.

A 30-day trial is the practical way to assess fit before committing. Zen Embedded trial downloads are full versions under a temporary 30-day license, which gives teams a defined evaluation window, not an ongoing free tier. The product-level custom pricing means buyers should establish which deployment and capacity they need before comparing costs.

Platforms

Zen spans Android, iOS, Linux, macOS, and Windows, as well as API and self-hosted deployments. That range is a good match for software that must share a database approach between mobile devices, edge systems, and larger environments. Enterprise platform support also includes Intel and ARM hardware, virtualization, and Docker.

Who it's for

Zen makes the most sense for developers and organizations embedding a database in products that need structured and semantic search together, especially where connectivity is intermittent or data must remain local. Its SQL and NoSQL interfaces, multiple deployment modes, and stated concurrent-user capacities make it relevant from remote field applications to larger enterprise workloads.

It is a less natural fit for someone seeking a free, standalone vector store or a simple pay-as-you-go experiment. Zen's embedded and relational scope is valuable when those are requirements, but the annual starting price and custom product pricing ask buyers to make a larger commitment than free alternatives do.

Pros and cons

• Pro: Relational filters can be combined with vector similarity, making Zen suitable for searches that need both semantic relevance and structured constraints.
• Pro: Offline search and AI-agent workflows support local and air-gapped use cases where cloud connectivity is not dependable or appropriate.
• Pro: Android and iOS support, plus broad desktop, server, and deployment options, can serve applications across mobile and enterprise environments.
• Con: There is no free plan, and the $417/mo (annual) starting price raises the cost of entry for teams that only need to explore vector search.
• Con: Custom pricing for the Zen plan makes it harder to judge total cost before discussing requirements with Actian.
• Con: The 30-day trial is time-limited, so it is not a substitute for a free tier in ongoing development or small-scale use.

Alternatives

For an open-source option with a free plan, consider Chroma: its maker says the same codebase powers its open-source database and Chroma Cloud. Zvec is another free alternative, an open-source in-process vector database under Apache License 2.0.

Pinecone may suit buyers who want a freemium API and web offering with a free Starter plan. Qdrant offers a free tier and API, cloud, and self-hosted platform options. For a defined free cloud allowance, Weaviate provides a free plan capped at 100,000 objects, 1 GB memory, and 10 GB disk.

Zilliz Cloud is worth considering for a free cloud cluster with 5 GB storage and up to 5 collections, while its Dedicated plan is pay as you go. Cloudflare Vectorize is a freemium API option with a Workers Free allowance for stored and queried vector dimensions. Vespa is a paid alternative with a free trial.

Browse more options in Vector Databases or Relational Databases.

Verdict

Choose Actian Zen if your application needs an embedded database that joins relational data, vector search, and offline operation across mobile, edge, and enterprise deployments. Its strongest reason to choose it is that combination, including local AI-agent workflows; its clearest reason to look elsewhere is the lack of a free plan and a $417/mo (annual) starting price. For buyers who can justify the broader database footprint, the 30-day full-version trial offers a concrete way to evaluate it.