DBMS > InterSystems Caché vs. Microsoft SQL Server vs. TimescaleDB vs. Titan vs. Vitess

System Properties Comparison InterSystems Caché vs. Microsoft SQL Server vs. TimescaleDB vs. Titan vs. Vitess

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.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

A multi-model DBMS and application server

Microsofts flagship relational DBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Titan is a Graph DBMS optimized for distributed clusters.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

Document store
Spatial DBMS

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.intersystems.com/products/cache

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

www.timescale.com

github.com/thinkaurelius/titan

vitess.io

Technical documentation

docs.intersystems.com

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

docs.timescale.com

github.com/thinkaurelius/titan/wiki

vitess.io/docs

Developer

InterSystems

Microsoft

Timescale

Aurelius, owned by DataStax

The Linux Foundation, PlanetScale

Initial release

1997

1989

2017

2012

2013

Current release

2018.1.4, May 2020

SQL Server 2022, November 2022

2.15.0, May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Apache license, version 2.0

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

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

Linux
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

depending on used data model

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

yes

with proprietary extensions

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
C++
Java

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

yes, across time and space (hash partitioning) attributes

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication with hot standby and reads on replicas

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

Relationships in graph

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

no user groups or roles

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