DBMS > Atos Standard Common Repository vs. Google BigQuery vs. Weaviate vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. Google BigQuery vs. Weaviate vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Large scale data warehouse service with append-only tables

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Relational DBMS

Vector DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

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

cloud.google.com/bigquery

github.com/weaviate/weaviate
weaviate.io

yaacomo.com

Technical documentation

cloud.google.com/bigquery/docs

weaviate.io/developers/weaviate

Developer

Atos Convergence Creators

Google

Weaviate B.V.

Q2WEB GmbH

Initial release

2016

2010

2019

2009

Current release

1703

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

commercial license available with Weaviate Enterprise

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux

hosted

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

yes, maps to GraphQL interface

yes

Typing

predefined data types such as float or date

optional

yes

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

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

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

yes

SQL

Support of SQL

yes

GraphQL is used as query language

yes

APIs and other access methods

LDAP

RESTful HTTP/JSON API

GraphQL query language
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Immediate Consistency

Eventual Consistency

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

Since BigQuery is designed for querying 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

User concepts

Access control

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

API Keys
OpenID Connect Discovery

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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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...
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Licensing and pricing models

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