DBMS > Atos Standard Common Repository vs. Couchbase vs. GreptimeDB vs. GridGain vs. SQream DB

System Properties Comparison Atos Standard Common Repository vs. Couchbase vs. GreptimeDB vs. GridGain vs. SQream DB

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

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

Technical documentation

docs.couchbase.com

docs.greptime.com

www.gridgain.com/docs/index.html

docs.sqream.com

Developer

Atos Convergence Creators

Couchbase, Inc.

Greptime Inc.

GridGain Systems, Inc.

SQream Technologies

Initial release

2016

2011

2022

2007

2017

Current release

1703

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

GridGain 8.5.1

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2.0

commercial

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, C++, Go and Erlang

Rust

Java, C++, .Net

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux
OS X
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

optional

yes

yes, ANSI Standard SQL 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

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

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

yes

APIs and other access methods

LDAP

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

gRPC
HTTP API
JDBC

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

.Net
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
Erlang
Go
Java
JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Python

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

user defined functions in Python

Triggers

yes

via the TAP protocol

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

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

Ephemeral buckets

yes

User concepts

Access control

LDAP bind authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Simple rights management via user accounts

Security Hooks for custom implementations

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