DBMS > Axibase vs. HBase vs. JanusGraph vs. Riak KV vs. Sadas Engine

System Properties Comparison Axibase vs. HBase vs. JanusGraph vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

axibase.com/docs/atsd/finance

hbase.apache.org

janusgraph.org

www.sadasengine.com

Technical documentation

hbase.apache.org/book.html

docs.janusgraph.org

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Axibase Corporation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Linux Foundation; originally developed as Titan by Aurelius

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Initial release

2013

2008

2017

2009

2006

Current release

15585

2.3.4, January 2021

0.6.3, February 2023

3.2.0, December 2022

8.0

License

Commercial or Open Source

commercial

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

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version 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

Erlang

C++

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X
Unix
Windows

Linux
OS X

AIX
Linux
Windows

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

options to bring your own types, AVRO

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

Clojure
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between data sets can be stored

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

User authentification and security via Rexster Graph Server

yes, using Riak Security

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

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