DBMS > Drizzle vs. Ignite vs. InfluxDB vs. mSQL vs. SQLite

System Properties Comparison Drizzle vs. Ignite vs. InfluxDB vs. mSQL vs. SQLite

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

DBMS for storing time series, events and metrics

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

ignite.apache.org

www.influxdata.com/products/influxdb-overview

hughestech.com.au/products/msql

www.sqlite.org

Technical documentation

apacheignite.readme.io/docs

docs.influxdata.com/influxdb

www.sqlite.org/docs.html

Developer

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Hughes Technologies

Dwayne Richard Hipp

Initial release

2008

2015

2013

1994

2000

Current release

7.2.4, September 2012

Apache Ignite 2.6

2.7.6, April 2024

4.4, October 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

free licenses can be provided

Open Source

Public Domain

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

C++

C++, Java, .Net

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

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

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

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

HTTP API
JSON over UDP

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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)

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes (replicated cache)

selectable replication factor

in enterprise version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

simple rights management via user accounts

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