DBMS > Apache Phoenix vs. Hypertable vs. Ignite vs. Microsoft SQL Server vs. Trafodion

System Properties Comparison Apache Phoenix vs. Hypertable vs. Ignite vs. Microsoft SQL Server vs. Trafodion

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Wide column store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

phoenix.apache.org

ignite.apache.org

www.microsoft.com/en-us/sql-server

trafodion.apache.org

Technical documentation

phoenix.apache.org

apacheignite.readme.io/docs

learn.microsoft.com/en-US/sql/sql-server

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Hypertable Inc.

Apache Software Foundation

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2014

2009

2015

1989

2014

Current release

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

0.9.8.11, March 2016

Apache Ignite 2.6

SQL Server 2022, November 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C++, Java, .Net

C++

C++, Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC

C++ API
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Supported programming languages

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

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java Stored Procedures

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor on file system level

yes (replicated cache)

yes, but depending on the SQL-Server Edition

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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