DBMS > Atos Standard Common Repository vs. JaguarDB vs. STSdb vs. Weaviate

System Properties Comparison Atos Standard Common Repository vs. JaguarDB vs. STSdb 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

Performant, highly scalable DBMS for AI and IoT applications

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

Document store
Key-value store

Key-value store
Vector DBMS

Key-value store

Vector DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

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

www.jaguardb.com

github.com/STSSoft/STSdb4

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.jaguardb.com/support.html

weaviate.io/developers/weaviate

Developer

Atos Convergence Creators

DataJaguar, Inc.

STS Soft SC

Weaviate B.V.

Initial release

2016

2015

2011

2019

Current release

1703

3.3 July 2023

4.0.8, September 2015

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

GPLv2, commercial license available

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++

the server part. Clients available in other languages

Server operating systems

Linux

Windows

Data scheme

Schema and schema-less with LDAP views

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

optional

yes

primitive types and user defined types (classes)

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

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

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

GraphQL is used as query language

APIs and other access methods

LDAP

JDBC
ODBC

.NET Client API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

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

LDAP bind authentication

rights management via user accounts

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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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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