DBMS > Atos Standard Common Repository vs. Bangdb vs. GridGain vs. Weaviate

System Properties Comparison Atos Standard Common Repository vs. Bangdb vs. GridGain vs. Weaviate

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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

Converged and high performance database for device data, events, time series, document and graph

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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

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

bangdb.com

www.gridgain.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.bangdb.com

www.gridgain.com/docs/index.html

weaviate.io/developers/weaviate

Developer

Atos Convergence Creators

Sachin Sinha, BangDB

GridGain Systems, Inc.

Weaviate B.V.

Initial release

2016

2012

2007

2019

Current release

1703

BangDB 2.0, October 2021

GridGain 8.5.1

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Open Source

commercial license available with Weaviate Enterprise

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++

Java, C++, .Net

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

optional

yes: string, long, double, int, geospatial, stream, events

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

secondary, composite, nested, reverse, geospatial

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL like support with command line tool

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

GraphQL is used as query language

APIs and other access methods

LDAP

Proprietary protocol
RESTful HTTP API

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

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

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

Triggers

yes

yes, Notifications (with Streaming only)

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

yes (replicated cache)

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual 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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

LDAP bind authentication

yes (enterprise version only)

Security Hooks for custom implementations

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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