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 NoSQL APIs. Also available eXtremeDB/rt a COTS real-time database management system that meets the fundamental requirements of determinism and temporal consistency of data.
eXtremeDB for HPC
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
C, C#, C++, Java, Lua, Python, Rust, SQL
SQL Anywhere, SQL Server, SQLBase, SQL/DS, SQLite
AIX, All OS with Java VM, Android, HP-UX, iOS, Linux, QNX, Solaris, VxWorks, Windows