DBMS > GridGain vs. Heroic vs. SAP Advantage Database Server vs. Tkrzw

System Properties Comparison GridGain vs. Heroic vs. SAP Advantage Database Server vs. Tkrzw

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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

Low-cost RDBMS with access to ISAM and FoxPro data structures

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store

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

Score	1.92
Rank	#126	Overall
	#25	Key-value stores
	#62	Relational DBMS

Score	0.25
Rank	#280	Overall
	#22	Time Series DBMS

Score	3.66
Rank	#91	Overall
	#48	Relational DBMS

Score	0.00
Rank	#363	Overall
	#57	Key-value stores

Website

www.gridgain.com

spotify.github.io/heroic/#!/index

www.sap.com/products/advantage-database-server.html

dbmx.net/tkrzw

Technical documentation

www.gridgain.com/docs/latest

spotify.github.io/heroic/#!/docs/overview

Developer

GridGain Systems, Inc.

Spotify

Sybase, SAP

Mikio Hirabayashi

Initial release

2007

2014

1993

2020

Current release

GridGain 8.5.1

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Delphi
Perl
PHP

C++
Java
Python
Ruby

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

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

caching of (temporary) tables can be configured

yes

using specific database classes

User concepts

Access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

GridGain Continues Strong Momentum in 2021, Has Record Revenue Year
22 February 2022, GlobeNewswire

HTAP-Enabling In-Memory Computing Technologies Market 2022 New Research Focusing on Industry Drivers | MongoDB, SAP, GigaSpaces Technologies, DataStax and IBM – Indian Defence News
19 June 2022, Indian Defence News

GridGain Announces Virtual Apache Ignite Summit 2022, Opens Call for Papers
7 February 2022, GlobeNewswire

HTAP-Enabling In-Memory Computing Technologies Market worth $7.3 billion by 2027 -Microsoft, IBM, MongoDB, SAP, Aerospike, DataStax, GridGain – Indian Defence News
12 June 2022, Indian Defence News

In Memory Computing Market 2022 – New Technology Innovation, Global Sales Analysis, Future Expansion, Business Overview, Opportunities Analysis & Demand Forecast to 2028
8 June 2022, Digital Journal

provided by Google News

Job opportunities

Customer Support Engineer
GridGain, Chicago, IL

Account Manager
GridGain, Indianapolis, IN

Senior Consultant
GridGain, Chicago, IL

Solutions Architect
GridGain, Pittsburgh, PA

Senior Software Architect
GridGain, Chicago, IL

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