DBMS > Axibase vs. RethinkDB vs. Splice Machine vs. XTDB

System Properties Comparison Axibase vs. RethinkDB vs. Splice Machine vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

axibase.com/docs/atsd/finance

rethinkdb.com

splicemachine.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

rethinkdb.com/docs

splicemachine.com/how-it-works

www.xtdb.com/docs

Developer

Axibase Corporation

The Linux Foundation

since July 2017

Splice Machine

Juxt Ltd.

Initial release

2013

2009

2014

2019

Current release

15585

2.4.1, August 2020

3.1, March 2021

1.19, September 2021

License

Commercial or Open Source

commercial

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

Open Source

Apache Version 2

Open Source

AGPL 3.0, commercial license available

Open Source

MIT License

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

C++

Java

Clojure

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, binary, float, bool, date, geometry

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

HTTP REST
JDBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes, each node contains all data

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

yes

users and table-level permissions

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

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More resources

DB-Engines blog posts

Meet some database management systems you are likely to hear more about in the future
4 August 2014, Paul Andlinger

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