DBMS > Axibase vs. OpenTenBase vs. Oracle Rdb vs. Splice Machine

System Properties Comparison Axibase vs. OpenTenBase vs. Oracle Rdb vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

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

An enterprise-level distributed HTAP open source database based on PostgreSQL

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

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

axibase.com/docs/atsd/finance

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

www.oracle.com/database/technologies/related/rdb.html

splicemachine.com

Technical documentation

docs.opentenbase.org
docs.opentenbase.org/en

www.oracle.com/database/technologies/related/rdb-doc.html

splicemachine.com/how-it-works

Developer

Axibase Corporation

OpenAtom Foundation, previously Tencent

Oracle, originally developed by Digital Equipment Corporation (DEC)

Splice Machine

Initial release

2013

1984

2014

Current release

15585

2.5, January 2024

7.4.1.1, 2021

3.1, March 2021

License

Commercial or Open Source

commercial

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

Open Source

BSD-3

commercial

Open Source

AGPL 3.0, commercial license available

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

Server operating systems

Linux

HP Open VMS

Linux
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
Go
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

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