DBMS > HBase vs. Microsoft Azure Cosmos DB vs. Riak KV vs. Splice Machine vs. STSdb

System Properties Comparison HBase vs. Microsoft Azure Cosmos DB vs. Riak KV vs. Splice Machine vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Distributed, fault tolerant key-value store

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

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

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

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

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

hbase.apache.org

azure.microsoft.com/services/cosmos-db

splicemachine.com

github.com/STSSoft/STSdb4

Technical documentation

hbase.apache.org/book.html

learn.microsoft.com/azure/cosmos-db

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

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

OpenSource, formerly Basho Technologies

Splice Machine

STS Soft SC

Initial release

2008

2014

2009

2014

2011

Current release

2.3.4, January 2021

3.2.0, December 2022

3.1, March 2021

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

hosted

Linux
OS X

Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

JSON types

yes

primitive types and user defined types (classes)

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

All properties auto-indexed by default

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API
Native Erlang Interface

JDBC
Native Spark Datasource
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
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

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

C#
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

JavaScript

Erlang

yes

Java

Triggers

yes

JavaScript

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

selectable replication factor

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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)

Multi-item ACID transactions with snapshot isolation within a partition

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 capabilities

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

yes

User concepts

Access control

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

Access rights can be defined down to the item level

yes, using Riak Security

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

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