DBMS > Apache Impala vs. mSQL vs. Riak TS vs. RocksDB

System Properties Comparison Apache Impala vs. mSQL vs. Riak TS vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

mSQL (Mini SQL) is a simple and lightweight RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

impala.apache.org

hughestech.com.au/products/msql

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

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

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hughes Technologies

Open Source, formerly Basho Technologies

Facebook, Inc.

Initial release

2013

1994

2015

2013

Current release

4.1.0, June 2022

4.4, October 2021

3.0.0, September 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free licenses can be provided

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C++

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes, limited

APIs and other access methods

JDBC
ODBC

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Delphi
Java
Perl
PHP
Tcl

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++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

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