DBMS > GridGain vs. Microsoft Azure Cosmos DB vs. OpenTSDB vs. Sphinx vs. TerminusDB

System Properties Comparison GridGain vs. Microsoft Azure Cosmos DB vs. OpenTSDB vs. Sphinx vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Globally distributed, horizontally scalable, multi-model database service

Scalable Time Series DBMS based on HBase

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Search engine

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.gridgain.com

azure.microsoft.com/services/cosmos-db

opentsdb.net

sphinxsearch.com

terminusdb.com

Technical documentation

www.gridgain.com/docs/index.html

learn.microsoft.com/azure/cosmos-db

opentsdb.net/docs/build/html/index.html

sphinxsearch.com/docs

terminusdb.github.io/terminusdb/#

Developer

GridGain Systems, Inc.

Microsoft

currently maintained by Yahoo and other contributors

Sphinx Technologies Inc.

DataChemist Ltd.

Initial release

2007

2014

2011

2001

2018

Current release

GridGain 8.5.1

3.5.1, February 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

GPL version 2, commercial licence available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

Java

C++

Prolog, Rust

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

numeric data for metrics, strings for tags

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

full-text index on all search fields

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

SQL-like query language (SphinxQL)

SQL-like query language (WOQL)

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

HTTP API
Telnet API

Proprietary protocol

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

Erlang
Go
Java
Python
R
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

yes

Triggers

yes (cache interceptors and events)

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Sharding

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

Role-based access control

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