DBMS > AntDB vs. FatDB vs. Microsoft Azure Table Storage vs. Weaviate vs. Yaacomo

System Properties Comparison AntDB vs. FatDB vs. Microsoft Azure Table Storage vs. Weaviate vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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

Description

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A Wide Column Store for rapid development using massive semi-structured datasets

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

Relational DBMS

Document store
Key-value store

Wide column store

Vector DBMS

Relational DBMS

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

Score	0.09
Rank	#342	Overall
	#149	Relational DBMS

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

azure.microsoft.com/en-us/services/storage/tables

github.com/weaviate/weaviate
weaviate.io

yaacomo.com

Technical documentation

weaviate.io/developers/weaviate

Developer

AsiaInfo Technologies Limited

FatCloud

Microsoft

Weaviate B.V.

Q2WEB GmbH

Initial release

2012

2019

2009

Current release

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

Server operating systems

Windows

hosted

Android
Linux
Windows

Data scheme

yes

schema-free

yes, maps to GraphQL interface

yes

Typing

predefined data types such as float or date

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.

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

SQL2016 compliant

Via inetgration in SQL Server

GraphQL is used as query language

yes

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

Can implement custom security layer via applications

Access rights based on private key authentication or shared access signatures

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,...
» 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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

AntDB: Answer to Database Evolution - Hyperconverged All-in-One Streaming Engine
22 June 2023, Bei Mo, AntDB (sponsor)

show all

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

show all

Recent citations in the news

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage
5 May 2015, Microsoft

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Testing Precompiled Azure Functions Locally with Storage Emulator
8 March 2018, Visual Studio Magazine

provided by Google News

Vector database startup Weaviate debuts ‘AI workbench’ and flexible storage tiers
30 July 2024, SiliconANGLE News

Weaviate Achieves Amazon Web Services GenAI Competency Status
8 July 2024, GlobeNewswire

Weaviate Enhances Cloud Console with New Collections and Explorer Tools for AI Developers
31 July 2024, Datanami

StructuredRAG Released by Weaviate: A Comprehensive Benchmark to Evaluate Large Language Models’ Ability to Generate Reliable JSON Outputs for Complex AI Systems
26 August 2024, MarkTechPost

Weaviate Raises $50 Million Series B Funding to Meet Soaring Demand for AI Native Vector Database Technology
21 April 2023, PR Newswire

provided by Google News

Share this page