ExtremeDB

Core offering, designed to be integrated directly into applications.

Allows developers to define tables as in-memory (for speed) or persistent (for durability on disk/flash), balancing performance with storage costs.

Supports deployments from tiny embedded devices at the edge to large cloud-based systems.

Can operate as a standalone embedded database or as part of a distributed system.

A high-performance implementation of ANSI SQL (broad coverage of SQL-89 standard) accessible directly or via ODBC/JDBC. Includes eXtremeDB-specific extensions for native data types, distributed queries, and a library of over 150 vector-based functions for time-series analytics.

Offers highly optimized, type-safe APIs for C, C++, Java, C#, Python, and Lua, allowing direct data manipulation for maximum performance and control.

Unique feature for robust data exchange between IoT edge devices and remote systems, handling intermittent connections and multi-tier replication (edge-to-gateway-to-cloud).

Supports horizontal partitioning of data across multiple nodes for scalability in distributed deployments.

Guarantees Atomicity, Consistency, Isolation, and Durability for all database operations, ensuring data integrity.

Supports both Multiple-Reader, Single-Writer (MURSIW) locking and Multi-Version Concurrency Control (MVCC) for flexible transaction management based on workload.

Eliminates file system I/O, multiple data copies, and redundant processes (like caching) for high performance.

Code size as small as 150KB for the core engine, minimizing memory demands and enabling lower-cost hardware.

Runs on a wide range of operating systems (Windows, Linux, many Unix variants, VxWorks, INTEGRITY, ThreadX, eCos, QNX, Android, iOS) and CPUs (x86, PowerPC, ARM, MIPS).

Specialized features for managing time-series data, including columnar (vertical) storage for sequences data type and a library of over 150 vector-based statistical functions.

Optimizes performance for time-series analysis by chaining functions to minimize data transfers.

Supports B-tree, R-tree (geospatial), Hash table, Radix tree (Patricia trie), k-d tree, Trigram index (text), and custom indexes.

Supports N-ary Storage Model (row-oriented) and Decomposition Storage Model (columnar) for sequences data. Hybrid designs possible.

Includes page-level Cyclic Redundancy Checking (CRC) for data integrity, AES encryption, and Secure Sockets Layer (SSL).

Notifies applications when specific database changes occur, supporting synchronous and asynchronous modes.

Records database changes for recovery in case of system failure.

Facilitates fine-grained data sharing between eXtremeDB applications and external enterprise DBMSs.

Allows modifying the database schema without requiring a full data dump and reload.

Proven in Network & Telecom, Consumer Electronics, Industrial Systems, Aerospace & Defense, Energy, Finance, Big Data & Analytics, and general Embedded Systems.

A management tool for SQL database management, including a visual network discovery tool.

Supports backing up databases while they are in use.

Offers transparency and deep control for developers.

Provides predictable performance for SQL queries, crucial for real-time systems.

Supports stored procedures written in Lua, Python, or C/C++ to reduce client-server communication.

Integrates with Active Directory and offers granular access control.

Includes Zip-like compression for tables and Run-length Encoding for time-series data.

Allows applications to influence cache policies beyond typical LRU to minimize retrieval overhead for time-sensitive data.