DBMS > H2GIS vs. OpenQM vs. Spark SQL vs. STSdb vs. Weaviate

System Properties Comparison H2GIS vs. OpenQM vs. Spark SQL vs. STSdb vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

QpenQM is a high-performance, self-tuning, multi-value DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Secondary database models

Relational DBMS

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

www.h2gis.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.h2gis.org/docs/home

spark.apache.org/docs/latest/sql-programming-guide.html

weaviate.io/developers/weaviate

Developer

CNRS

Rocket Software, originally Martin Phillips

Apache Software Foundation

STS Soft SC

Weaviate B.V.

Initial release

2013

1993

2014

2011

2019

Current release

3.4-12

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

1.19, May 2023

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

GPLv2, extended commercial license available

Open Source

Apache 2.0

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

Scala

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

Windows

Data scheme

yes

with some exceptions

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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

yes

SQL-like DML and DDL statements

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC

.NET Client API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java

.Net
Basic
C
Java
Objective C
PHP
Python

Java
Python
R
Scala

C#
Java

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

none

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, 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

yes

based on H2

Access rights can be defined down to the item level

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...
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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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