DBMS > GridGain vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Rockset vs. TigerGraph

System Properties Comparison GridGain vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. Rockset vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

A scalable, reliable search and analytics service in the cloud, built on RocksDB

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Key-value store
Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Graph DBMS

Secondary database models

Spatial DBMS

Relational DBMS
Search engine

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.gridgain.com

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

rockset.com

www.tigergraph.com

Technical documentation

www.gridgain.com/docs/index.html

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

docs.rockset.com

docs.tigergraph.com

Developer

GridGain Systems, Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Rockset

Initial release

2007

2010

2014

2019

2017

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

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

Erlang

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

all fields are automatically indexed

SQL

Support of SQL

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

SQL-like query language

Read-only SQL queries, including JOINs

SQL-like query language (GSQL)

APIs and other access methods

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

RESTful HTTP/JSON API

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

HTTP REST

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Go
Java
JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

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

View functions (Map-Reduce) in JavaScript

JavaScript

yes

Triggers

yes (cache interceptors and events)

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

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

Security Hooks for custom implementations

Access rights for users can be defined per database

Access rights can be defined down to the item level

Access rights for users and organizations can be defined via Rockset console

Role-based access control

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