DBMS > Apache Phoenix vs. IBM Db2 vs. Microsoft Azure Synapse Analytics vs. RocksDB

System Properties Comparison Apache Phoenix vs. IBM Db2 vs. Microsoft Azure Synapse Analytics vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key-value store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

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

Website

phoenix.apache.org

www.ibm.com/products/db2

azure.microsoft.com/services/synapse-analytics

rocksdb.org

Technical documentation

phoenix.apache.org

www.ibm.com/docs/en/db2

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

IBM

Microsoft

Facebook, Inc.

Initial release

2014

1983

host version

2016

2013

Current release

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

12.1, October 2016

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

Open Source

BSD

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

C and C++

C++

Server operating systems

Linux
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

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

SQL

Support of SQL

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

fine grained access rights according to SQL-standard

yes

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