DBMS > Axibase vs. Splice Machine vs. TerminusDB vs. VelocityDB

System Properties Comparison Axibase vs. Splice Machine vs. TerminusDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Website

axibase.com/docs/atsd/finance

splicemachine.com

terminusdb.com

velocitydb.com

Technical documentation

splicemachine.com/how-it-works

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Axibase Corporation

Splice Machine

DataChemist Ltd.

VelocityDB Inc

Initial release

2013

2014

2018

2011

Current release

15585

3.1, March 2021

11.0.0, January 2023

7.x

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Prolog, Rust

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux

Any that supports .NET

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript
Python

.Net

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Role-based access control

Based on Windows Authentication

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