DBMS > Apache Phoenix vs. IBM Db2 vs. Spark SQL vs. SQLite vs. Transbase

System Properties Comparison Apache Phoenix vs. IBM Db2 vs. Spark SQL vs. SQLite vs. Transbase

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

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

Primary database model

Relational DBMS

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

Relational DBMS

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	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

phoenix.apache.org

www.ibm.com/products/db2

spark.apache.org/sql

www.sqlite.org

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

Technical documentation

phoenix.apache.org

www.ibm.com/docs/en/db2

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

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

Developer

Apache Software Foundation

IBM

Apache Software Foundation

Dwayne Richard Hipp

Transaction Software GmbH

Initial release

2014

1983

host version

2014

2000

1987

Current release

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

12.1, October 2016

3.5.0 ( 2.13), September 2023

3.46.0 (23 May 2024), May 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

Open Source

Apache 2.0

Open Source

Public Domain

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

Java

C and C++

Scala

C and C++

Server operating systems

Linux
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Windows

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC
Proprietary native 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

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

with separate tools (MQ, InfoSphere)

none

Source-replica replication

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

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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