DBMS > GridGain vs. IBM Db2 warehouse vs. InfluxDB vs. PouchDB vs. SQLite

System Properties Comparison GridGain vs. IBM Db2 warehouse vs. InfluxDB vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Cloud-based data warehousing service

DBMS for storing time series, events and metrics

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.gridgain.com

www.ibm.com/products/db2/warehouse

www.influxdata.com/products/influxdb-overview

pouchdb.com

www.sqlite.org

Technical documentation

www.gridgain.com/docs/index.html

docs.influxdata.com/influxdb

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

GridGain Systems, Inc.

IBM

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2007

2014

2013

2012

2000

Current release

GridGain 8.5.1

2.7.6, April 2024

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

Public Domain

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, C++, .Net

JavaScript

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
OS X

through Homebrew

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Import/export of XML data possible

Secondary indexes

yes

via views

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

.NET Client API
JDBC
ODBC
OLE DB

HTTP API
JSON over UDP

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript

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

yes (compute grid and cache interceptors can be used instead)

PL/SQL, SQL PL

View functions in JavaScript

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

selectable replication factor

in enterprise version only

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

An Introductory Guide to Grafana Alerts
16 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 2024

A Detailed Guide to C# TimeSpan
2 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.