DBMS > Microsoft Azure Cosmos DB vs. Sphinx vs. TimesTen vs. TinkerGraph

System Properties Comparison Microsoft Azure Cosmos DB vs. Sphinx vs. TimesTen vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Open source search engine for searching in data from different sources, e.g. relational databases

In-Memory RDBMS compatible to Oracle

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Score	0.12
Rank	#344	Overall
	#34	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

sphinxsearch.com

www.oracle.com/database/technologies/related/timesten.html

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

learn.microsoft.com/azure/cosmos-db

sphinxsearch.com/docs

docs.oracle.com/database/timesten-18.1

Developer

Microsoft

Sphinx Technologies Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2001

1998

2009

Current release

3.5.1, February 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

commercial

Open Source

Apache 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

C++

Java

Server operating systems

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

yes

APIs and other access methods

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

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

TinkerPop 3

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C++
Java
PL/SQL

Groovy
Java

Server-side scripts

Stored procedures

JavaScript

PL/SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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 or Eventual Consistency depending on configuration

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

by means of logfiles and checkpoints

optional

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 can be defined down to the item level

fine grained access rights according to SQL-standard

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