DBMS > Apache Pinot vs. IBM Cloudant vs. LeanXcale vs. Linter

System Properties Comparison Apache Pinot vs. IBM Cloudant vs. LeanXcale vs. Linter

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Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

RDBMS for high security requirements

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Website

pinot.apache.org

www.ibm.com/products/cloudant

www.leanxcale.com

linter.ru

Technical documentation

docs.pinot.apache.org

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation and contributors

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

LeanXcale

relex.ru

Initial release

2015

2010

2015

1990

Current release

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C and C++

Server operating systems

All OS with a Java JDK11 or higher

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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 can be defined per database

fine grained access rights according to SQL-standard

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More resources

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