DBMS > Apache Pinot vs. EXASOL vs. IBM Cloudant vs. Microsoft SQL Server

System Properties Comparison Apache Pinot vs. EXASOL vs. IBM Cloudant vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Database as a Service offering based on Apache CouchDB

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

pinot.apache.org

www.exasol.com

www.ibm.com/products/cloudant

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

Technical documentation

docs.pinot.apache.org

www.exasol.com/resources

cloud.ibm.com/docs/Cloudant

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

Developer

Apache Software Foundation and contributors

Exasol

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2015

2000

2010

1989

Current release

1.0.0, September 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

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

Erlang

C++

Server operating systems

All OS with a Java JDK11 or higher

hosted

Linux
Windows

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

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

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

Supported programming languages

Go
Java
Python

Java
Lua
Python
R

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Server-side scripts

Stored procedures

user defined functions

View functions (Map-Reduce) in JavaScript

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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 according to SQL-standard

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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