DBMS > GridGain vs. Heroic vs. Microsoft Azure Cosmos DB vs. OpenQM

System Properties Comparison GridGain vs. Heroic vs. Microsoft Azure Cosmos DB vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Globally distributed, horizontally scalable, multi-model database service

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Multivalue DBMS

Secondary database models

Spatial DBMS

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	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

www.gridgain.com

github.com/spotify/heroic

azure.microsoft.com/services/cosmos-db

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

www.gridgain.com/docs/index.html

spotify.github.io/heroic

learn.microsoft.com/azure/cosmos-db

Developer

GridGain Systems, Inc.

Spotify

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2007

2014

1993

Current release

GridGain 8.5.1

3.4-12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

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, C++, .Net

Java

Server operating systems

Linux
OS X
Solaris
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

Typing

predefined data types such as float or date

yes

JSON types

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

via Elasticsearch

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

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

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

.Net
Basic
C
Java
Objective C
PHP
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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Implicit feature of the cloud service

yes

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

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

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

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