DBMS > Apache Impala vs. HBase vs. Riak TS vs. SQream DB

System Properties Comparison Apache Impala vs. HBase vs. Riak TS vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

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	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

impala.apache.org

hbase.apache.org

sqream.com

Technical documentation

impala.apache.org/impala-docs.html

hbase.apache.org/book.html

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

docs.sqream.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Open Source, formerly Basho Technologies

SQream Technologies

Initial release

2013

2008

2015

2017

Current release

4.1.0, June 2022

2.3.4, January 2021

3.0.0, September 2022

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

commercial

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

C++

Java

Erlang

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
OS X

Linux

Data scheme

yes

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes, ANSI Standard SQL Types

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

yes, limited

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

HTTP API
Native Erlang Interface

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

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++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Coprocessors in Java

Erlang

user defined functions in Python

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

none

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

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

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

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

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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13 May 2013, Paul Andlinger

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