DBMS > Apache Impala vs. Apache Phoenix vs. Citus vs. Transbase

System Properties Comparison Apache Impala vs. Apache Phoenix vs. Citus vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A scale-out RDBMS with evolutionary schema built on Apache HBase

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

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	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

impala.apache.org

phoenix.apache.org

www.citusdata.com

www.transaction.de/en/products/transbase.html

Technical documentation

impala.apache.org/impala-docs.html

phoenix.apache.org

docs.citusdata.com

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Transaction Software GmbH

Initial release

2013

2014

2010

1987

Current release

4.1.0, June 2022

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

8.1, December 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

AGPL, commercial license also available

commercial

free development 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

C++

Java

C and C++

Server operating systems

Linux

Linux
Unix
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard, with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

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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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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

provided by Google News

Ubicloud wants to build an open source alternative to AWS
5 March 2024, TechCrunch

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL ...
24 January 2019, Microsoft

Ubicloud reels in $16M for its open-source cloud platform
5 March 2024, SiliconANGLE News

Distributed PostgreSQL Benchmarks: Azure Cosmos DB, CockroachDB, and YugabyteDB
8 July 2023, InfoQ.com

Microsoft Benchmarks Distributed PostgreSQL DBs
10 July 2023, Datanami

provided by Google News

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