Indexes

B+Tree Hash Table R-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)

Query Interface

Custom API SQL Stored Procedures HTTP / REST Command-line / Shell RPC

Compression

Run-Length Encoding

Database pages are stored in a compressed format and decompressed when accessed by the application. This can maximize available storage space, which could be important for an in-memory database, or even a persistent database stored on a relatively small SSD. Run-length encoding (RLE) compression is applied to time series data (i.e. fields defined as the ‘sequence’ data type). In McObject’s tests, activating this feature reduced storage space requirements by 75% and increased speed in reading the database by 21%. Compression and RLE are separate features that can be used individually. Data can also be compressed between server and device in eXtremeDB’s Active Replication Fabric for IoT networks. Operating in low-bandwidth networks requires techniques to compress the network traffic. To solve this problem for all network components of eXtremeDB at once, the compression is implemented at the system abstraction layer (SAL).

System Architecture

Shared-Nothing Shared-Memory Embedded

Storage Model

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.

Concurrency Control

Multi-version Concurrency Control (MVCC) Optimistic Concurrency Control (OCC)

eXtremeDB offers a multi-version concurrency control (MVCC) optimistic transaction manager and an alternative “pessimistic” MURSIW (MUltiple Reader, Single Writer) transaction manager.

Data Model

Relational

Stored Procedures

Supported

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.

Foreign Keys

Supported

Query Compilation

JIT Compilation Stored Procedure Compilation

Storage Architecture

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.

Isolation Levels

Read Committed Serializable Repeatable Read