DBMS > Apache Pinot vs. BigchainDB vs. IBM Db2 vs. Microsoft SQL Server vs. Trafodion

System Properties Comparison Apache Pinot vs. BigchainDB vs. IBM Db2 vs. Microsoft SQL Server vs. Trafodion

Editorial information provided by DB-Engines

Name

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

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store

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

Document store
Graph DBMS
Spatial DBMS

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

pinot.apache.org

www.bigchaindb.com

www.ibm.com/products/db2

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

trafodion.apache.org

Technical documentation

docs.pinot.apache.org

bigchaindb.readthedocs.io/en/latest

www.ibm.com/docs/en/db2

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

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation and contributors

IBM

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2015

2016

1983

host version

1989

2014

Current release

1.0.0, September 2023

12.1, October 2016

SQL Server 2022, November 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

commercial

free version is available

commercial

restricted free version is available

Open Source

Apache 2.0

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

Python

C and C++

C++

C++, Java

Server operating systems

All OS with a Java JDK11 or higher

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

Linux

Data scheme

yes

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

CLI Client
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

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

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

yes

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

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

only with Windows/Unix/Linux Version

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

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