DBMS > Memcached vs. Microsoft Azure Cosmos DB vs. SAP SQL Anywhere vs. Splunk vs. Titan

System Properties Comparison Memcached vs. Microsoft Azure Cosmos DB vs. SAP SQL Anywhere vs. Splunk 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

Globally distributed, horizontally scalable, multi-model database service

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Analytics Platform for Big Data

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Search engine

Graph DBMS

Secondary database models

Spatial DBMS

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

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

www.memcached.org

azure.microsoft.com/services/cosmos-db

www.sap.com/products/technology-platform/sql-anywhere.html

www.splunk.com

github.com/thinkaurelius/titan

Technical documentation

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

help.sap.com/docs/SAP_SQL_Anywhere

docs.splunk.com/Documentation/Splunk

github.com/thinkaurelius/titan/wiki

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

SAP

formerly Sybase

Splunk Inc.

Aurelius, owned by DataStax

Initial release

2003

2014

1992

2003

2012

Current release

1.6.27, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

BSD license

commercial

Limited free edition and free developer edition available

Open Source

Apache license, version 2.0

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

Java

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
HTTP API
JDBC
ODBC

HTTP REST

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

JavaScript

yes, in C/C++, Java, .Net or Perl

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

Source-replica replication

Database mirroring

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles

User authentification and security via Rexster Graph Server

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