DBMS > Apache Druid vs. H2 vs. InterSystems Caché vs. Microsoft SQL Server vs. Netezza

System Properties Comparison Apache Druid vs. H2 vs. InterSystems Caché vs. Microsoft SQL Server vs. Netezza

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A multi-model DBMS and application server

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

druid.apache.org

www.h2database.com

www.intersystems.com/products/cache

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

www.ibm.com/products/netezza

Technical documentation

druid.apache.org/docs/latest/design

www.h2database.com/html/main.html

docs.intersystems.com

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

Developer

Apache Software Foundation and contributors

Thomas Mueller

InterSystems

Microsoft

IBM

Initial release

2012

2005

1997

1989

2000

Current release

29.0.1, April 2024

2.2.220, July 2023

2018.1.4, May 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

included in appliance

Data scheme

yes

schema-less columns are supported

yes

depending on used data model

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C#
C++
Java

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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