DBMS > Apache Drill vs. IBM Db2 Event Store vs. InterSystems Caché vs. Microsoft Azure SQL Database vs. Stardog

System Properties Comparison Apache Drill vs. IBM Db2 Event Store vs. InterSystems Caché vs. Microsoft Azure SQL Database vs. Stardog

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Distributed Event Store optimized for Internet of Things use cases

A multi-model DBMS and application server

Database as a Service offering with high compatibility to Microsoft SQL Server

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Event Store
Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

drill.apache.org

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

www.intersystems.com/products/cache

azure.microsoft.com/en-us/products/azure-sql/database

www.stardog.com

Technical documentation

drill.apache.org/docs

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

docs.intersystems.com

docs.microsoft.com/en-us/azure/azure-sql

docs.stardog.com

Developer

Apache Software Foundation

IBM

InterSystems

Microsoft

Stardog-Union

Initial release

2012

2017

1997

2010

Current release

1.20.3, January 2023

2.0

2018.1.4, May 2020

V12

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C and C++

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

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

hosted

Linux
macOS
Windows

Data scheme

schema-free

yes

depending on used data model

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

through the embedded Spark runtime

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C++

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

C#
C++
Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

yes, with always 3 replicas available

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

Depending on the underlying data source

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.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Access rights for users and roles

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