DBMS > Memcached vs. Microsoft SQL Server vs. SQream DB vs. TimescaleDB vs. Titan

System Properties Comparison Memcached vs. Microsoft SQL Server vs. SQream DB vs. TimescaleDB vs. Titan

Editorial information provided by DB-Engines

Name

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

In-memory key-value store, originally intended for caching

Microsofts flagship relational DBMS

a GPU-based, columnar RDBMS for big data analytics workloads

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.memcached.org

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

sqream.com

www.timescale.com

github.com/thinkaurelius/titan

Technical documentation

github.com/memcached/memcached/wiki

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

docs.sqream.com

docs.timescale.com

github.com/thinkaurelius/titan/wiki

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

SQream Technologies

Timescale

Aurelius, owned by DataStax

Initial release

2003

1989

2017

2012

Current release

1.6.27, May 2024

SQL Server 2022, November 2022

2022.1.6, December 2022

2.15.0, May 2024

License

Commercial or Open Source

Open Source

BSD license

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

APIs and other access methods

Proprietary protocol

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

.Net
JDBC
ODBC

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

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

user defined functions in Python

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

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

horizontal and vertical partitioning

yes, across time and space (hash partitioning) attributes

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

none

Source-replica replication with hot standby and reads on replicas

yes

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

Foreign keys

Referential integrity

yes

Relationships in graph

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

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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