DBMS > DataFS vs. Fujitsu Enterprise Postgres vs. TempoIQ vs. Weaviate

System Properties Comparison DataFS vs. Fujitsu Enterprise Postgres vs. TempoIQ vs. Weaviate

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

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

Primary database model

Secondary database models

Graph DBMS

Document store
Spatial DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

newdatabase.com

www.postgresql.fastware.com

tempoiq.com (offline)

github.com/weaviate/weaviate
weaviate.io

Technical documentation

dev.mobiland.com/Overview.xsp

www.postgresql.fastware.com/product-manuals

weaviate.io/developers/weaviate

Developer

Mobiland AG

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

TempoIQ

Weaviate B.V.

Initial release

2018

2012

2019

Current release

1.1.263, October 2022

Fujitsu Enterprise Postgres 14, January 2022

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

commercial license available with Weaviate Enterprise

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

Linux
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript

Node.js
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

partitioning by range, list and by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Windows-Profile

fine grained access rights according to SQL-standard

simple authentication-based access control

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

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

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

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

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

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

Key customers

All companies that have data.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

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

Licensing and pricing models

Core based licensing
» more

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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