DBMS > Drizzle vs. Elasticsearch vs. Ignite vs. Microsoft SQL Server

System Properties Comparison Drizzle vs. Elasticsearch vs. Ignite vs. Microsoft SQL Server

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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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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.

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Search engine

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.elastic.co/elasticsearch

ignite.apache.org

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

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

apacheignite.readme.io/docs

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

Developer

Drizzle project, originally started by Brian Aker

Elastic

Apache Software Foundation

Microsoft

Initial release

2008

2010

2015

1989

Current release

7.2.4, September 2012

8.6, January 2023

Apache Ignite 2.6

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Elastic License

Open Source

Apache 2.0

commercial

restricted free version is available

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++

Java

C++, Java, .Net

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

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

yes

APIs and other access methods

JDBC

Java API
RESTful HTTP/JSON API

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

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

Supported programming languages

C
C++
Java
PHP

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

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

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

Triggers

hooks for callbacks inside the server can be used.

yes

by using the 'percolation' feature

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes (replicated cache)

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate 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

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.

Memcached and Redis integration

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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