DBMS > Altibase vs. Amazon DynamoDB vs. GridGain vs. HugeGraph vs. Microsoft Azure Cosmos DB

System Properties Comparison Altibase vs. Amazon DynamoDB vs. GridGain vs. HugeGraph vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A fast-speed and highly-scalable Graph DBMS

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store
Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Website

altibase.com

aws.amazon.com/dynamodb

www.gridgain.com

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/dynamodb

www.gridgain.com/docs/index.html

hugegraph.apache.org/docs

learn.microsoft.com/azure/cosmos-db

Developer

Altibase

Amazon

GridGain Systems, Inc.

Baidu

Microsoft

Initial release

1999

2012

2007

2018

2014

Current release

v7.3, 2023, August 2023

GridGain 8.5.1

0.9

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

commercial

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, C++, .Net

Java

Server operating systems

AIX
HP-UX
Linux

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Unix

hosted

Data scheme

yes

schema-free

yes

schema-free

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

also supports composite index and range index

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI SQL-92

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

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

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

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Supported programming languages

C
C++
Java

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Groovy
Java
Python

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

Server-side scripts

Stored procedures

stored procedures and stored functions

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

asynchronous Gremlin script jobs

JavaScript

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

via hugegraph-spark

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

can be specified for read operations

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Security Hooks for custom implementations

Users, roles and permissions

Access rights can be defined down to the item level

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