eXtremeDB is a DBMS that supports both on-disk and in-memory databases. There are multiple editions of eXtremeDB that support time-series data, high availability, distributed databases, and SQL and NonSQL APIs.
eXtremeDB/rt is a commercial off-the-shelf deterministic realtime database management system that meets the fundamental requirements of determinism and temporal consistency of data. eXtremeDB/rt works together with the RTOS to ensure that tasks complete within their CPU budgets and transaction deadlines.
eXtremeDB for High Performance Computing was developed for HPC systems and comes with a library of more than 100 functions for performing statistical analysis of time series data. Combine row-based and column-based layouts, in order to best leverage the CPU cache speed, and a pipelining technique where the output of one element is the input of the next.
The eXtremeDB IoT Software Development Kit has the capability to replicate data from the edge to the server, including through many tiers (edge/gateway/server). Device and server communicate flawlessly. It offers encryption of data at rest and in flight, and provides support for time series data.
McObject started in 2001 with the launch of the eXtremeDB In-Memory Database System.
Custom API SQL Stored Procedures HTTP / REST Command-line / Shell RPC
Multi-version Concurrency Control (MVCC) Optimistic Concurrency Control (OCC) Deterministic Concurrency Control
eXtremeDB offers a multi-version concurrency control (MVCC) optimistic transaction manager and an alternative "pessimistic" MURSIW (MUltiple Reader, Single Writer) transaction manager.
Decomposition Storage Model (Columnar) N-ary Storage Model (Row/Record) Hybrid
eXtremeDB implements row-based layout for all data types other than sequences. Row and columnar layout can be combined in hybrid data designs to optimize performance managing mixed data.
Read Committed Serializable Repeatable Read
Lua, Python or C++ based stored procedures run in the context of the SQL server and therefore minimizes client-server inter-process communication and attendant network overhead, and fully utilizes the multi-core nature of modern hardware.
B+Tree Hash Table R-Tree T-Tree K-D Tree Patricia/Radix Trie
eXtremeDB database offers multiple indexes, including the following:
B-Trees for common sorting and searches, insertions, and deletions R-Trees for geospatial indexing (common in GPS/navigation systems) Hash tables for quickly locating a single unique index entry Patricia trie index, which speeds searches in networking and telephony applications Trigram indexes are ideal for text searches when the exact spelling of the target object is not precisely known. It finds objects which match the maximum number of three-character strings in the entered search terms, i.e., near matches. “Custom indexes” or b-trees that allow the application to define the collating sequence of entries; this is useful in implementing soundex algorithm searches, for example KD-Trees or k-dimensional trees, for spatial and pattern-matching tasks and in applications where query predicates contain various combinations of object fields (for example, to construct Query-By-Example, or QBE features)
Disk-oriented In-Memory Hybrid
eXtremeDB enables the developer to combine both database paradigms – in-memory and on-disk – in a single database instance. Specifying one set of data as transient (managed in memory), while choosing persistent storage for other record types, requires a simple database schema declaration.
Shared-Nothing Shared-Memory Embedded
JIT Compilation Stored Procedure Compilation
As well as Prepared Statements
Run-Length Encoding Naïve (Page-Level)
eXtremeDB offers Zip-like compression for tables (horizontal storage), and Run-length Encoding for time series (vertical storage).
C, C#, C++, Java, Lua, Python, Rust, SQL
AIX, All OS with Java VM, Android, HP-UX, iOS, Linux, QNX, Solaris, VxWorks, Windows