DBMS > Atos Standard Common Repository vs. EventStoreDB vs. GridGain vs. HarperDB vs. SAP HANA

System Properties Comparison Atos Standard Common Repository vs. EventStoreDB vs. GridGain vs. HarperDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Key-value store

Event Store

Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.eventstore.com

www.gridgain.com

www.harperdb.io

www.sap.com/products/hana.html

Technical documentation

developers.eventstore.com

www.gridgain.com/docs/index.html

docs.harperdb.io/docs

help.sap.com/hana

Developer

Atos Convergence Creators

Event Store Limited

GridGain Systems, Inc.

HarperDB

SAP

Initial release

2016

2012

2007

2017

2010

Current release

1703

21.2, February 2021

GridGain 8.5.1

3.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

commercial

free community edition available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net

Node.js

Server operating systems

Linux

Linux
Windows

Linux
OS X
Solaris
Windows

Linux
OS X

Appliance or cloud-service

Data scheme

Schema and schema-less with LDAP views

yes

dynamic schema

yes

Typing

predefined data types such as float or date

optional

yes

JSON data types

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

SQL

Support of SQL

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

SQL-like data manipulation statements

yes

APIs and other access methods

LDAP

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Server-side scripts

Stored procedures

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

Custom Functions

since release 3.1

SQLScript, R

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

A table resides as a whole on one (or more) nodes in a cluster

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

the nodes on which a table resides can be defined

yes

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

LDAP bind authentication

Security Hooks for custom implementations

Access rights for users and roles

yes

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