DBMS > GridGain vs. Heroic vs. MaxDB vs. Microsoft Azure AI Search

System Properties Comparison GridGain vs. Heroic vs. MaxDB vs. Microsoft Azure AI Search

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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

A robust and reliable RDBMS optimized to run all major SAP solutions

Search-as-a-service for web and mobile app development

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Search engine

Secondary database models

Vector DBMS

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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

www.gridgain.com

github.com/spotify/heroic

maxdb.sap.com

azure.microsoft.com/en-us/services/search

Technical documentation

www.gridgain.com/docs/index.html

spotify.github.io/heroic

maxdb.sap.com/documentation

learn.microsoft.com/en-us/azure/search

Developer

GridGain Systems, Inc.

Spotify

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Initial release

2007

2014

1984

2015

Current release

GridGain 8.5.1

7.9.10.12, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Limited community edition free

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

Java, C++, .Net

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

via Elasticsearch

yes

SQL

Support of SQL

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

yes

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

ADO.NET
JDBC
ODBC
WebDAV

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
Perl
PHP
Python

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

yes

using Azure authentication

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