eXtremeDB

Paid#7 of 24 in In-Memory DatabasesEmbedded Databases

eXtremeDB: A broad embedded database for durable, real-time, and distributed workloads. Ranked #7 of 24 in In-Memory Databases by our editors (8.5/10); pricing: Pricing on request · 60-day trial; best for embedded and edge applications needing durability.

8.5/10★★★★☆Editor score

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eXtremeDB8.5 Visit McObject

At a glance

• Editor score
  8.5 / 10
• Pricing
  Pricing on request · 60-day trial
• Best for
  Embedded and edge applications needing durability
• Deployment
  Both
• Founded
  2001 · Federal Way, Washington, USA
• Facts checked
  20 Sep 2026

• Where it wins

  • Supports in-memory, persistent, and hybrid storage modes
  • Combines replication, failover, clustering, and distributed queries
  • Offers SQL, native APIs, vector indexes, and time-series layouts

• Where it doesn't

  • Pricing requires contacting McObject's sales team
  • The 60-day offer is an evaluation trial, not a perpetual free plan
  • Its broad feature set may exceed the needs of simple embedded applications

Our verdict on eXtremeDB

eXtremeDB is an embedded database management system for professional developers building resource-constrained, real-time, IoT, networking, financial, and high-performance computing applications. It supports embedded and client/server architectures across Windows, macOS, Linux, iOS, Android, and API environments. Storage can be in-memory, persistent, or hybrid, while applications can use SQL interfaces, native language APIs, or object-based and time-series data models. It is a fit for teams that need database durability and processing flexibility close to an application or device.

For distributed and availability-sensitive systems, eXtremeDB combines synchronous or asynchronous replication with automatic failover, active/active clustering, distributed query processing, sharding, and change data capture. Transaction logging and incremental backup/restore add operational coverage, while RESTful web services, ODBC, JDBC, C/C++, Java, C#, Python, and Rust support different integration paths. These capabilities make it suitable for architectures that must coordinate data across embedded, edge, and client/server deployments rather than relying on a single local store.

The product also covers specialized workloads without limiting teams to one storage layout. Native approximate-nearest-neighbor indexes and vector-based statistical functions support vector workloads, while row-oriented and columnar time-series layouts address time-based data. McObject handles licensing through its sales team, and the available evaluation offer lasts 60 days; it is not a perpetual free plan. Choose eXtremeDB when embedded deployment, persistence, high availability, or mixed workload support matters. A simpler embedded database may be a better fit for applications that need only basic local storage and do not require these distributed, analytical, or durability features.

Your product? Our editors can test eXtremeDB in depth and publish a review, labelled as paid · from $149/mo →

eXtremeDB pricing

eXtremeDB fact sheet

eXtremeDB integrations

eXtremeDB lists 8 integrations on its own site.

• ODBC
• JDBC
• REST
• C/C++
• Java
• C#
• Python
• Rust

Alternatives to eXtremeDB

• Couchbase ServerA broad in-memory platform with free production use and extensive database capabilities.9.4
• Apache IgniteOpen-source distributed SQL with in-memory speed, persistence, transactions, and compute.9.2
• IInfinispanA Java-centric choice for clustered caching, persistence, replication, and search.9.0

See all eXtremeDB alternatives →

eXtremeDB vs the competition

• eXtremeDB vs Couchbase Server
• eXtremeDB vs Apache Ignite
• IeXtremeDB vs Infinispan
• eXtremeDB vs Aerospike Database
• eXtremeDB vs Valkey
• eXtremeDB vs Tarantool DB

Compare eXtremeDB with any tool side by side →

Featured on iTechGuides

eXtremeDB is listed in our In-Memory Databases directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update