DBMS > IBM Cloudant vs. IBM Db2 Event Store vs. JaguarDB vs. OpenMLDB vs. SQLite

System Properties Comparison IBM Cloudant vs. IBM Db2 Event Store vs. JaguarDB vs. OpenMLDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Distributed Event Store optimized for Internet of Things use cases

Performant, highly scalable DBMS for AI and IoT applications

An open-source machine learning database that provides a feature platform for training and inference

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Event Store
Time Series DBMS

Key-value store
Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/cloudant

www.ibm.com/products/db2-event-store

www.jaguardb.com

openmldb.ai

www.sqlite.org

Technical documentation

cloud.ibm.com/docs/Cloudant

www.ibm.com/docs/en/db2-event-store

www.jaguardb.com/support.html

openmldb.ai/docs/zh/main

www.sqlite.org/docs.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

IBM

DataJaguar, Inc.

4 Paradigm Inc.

Dwayne Richard Hipp

Initial release

2010

2017

2015

2020

2000

Current release

2.0

3.3 July 2023

2024-2 February 2024

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL V3.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C and C++

C++

the server part. Clients available in other languages

C++, Java, Scala

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux

server-less

Data scheme

schema-free

yes

Fixed schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

through the embedded Spark runtime

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

JDBC
SQLAlchemy

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Go
Java
Python
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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Active-active shard replication

Multi-source replication

Source-replica replication

none

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

No - written data is immutable

yes

via file-system locks

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

rights management via user accounts

fine grained access rights according to SQL-standard

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