DBMS > Heroic vs. OpenQM vs. Quasardb vs. SWC-DB vs. Weaviate

System Properties Comparison Heroic vs. OpenQM vs. Quasardb vs. SWC-DB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Distributed, high-performance timeseries database

A high performance, scalable Wide Column DBMS

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

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

github.com/spotify/heroic

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

quasar.ai

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

spotify.github.io/heroic

doc.quasar.ai/master

weaviate.io/developers/weaviate

Developer

Spotify

Rocket Software, originally Martin Phillips

quasardb

Alex Kashirin

Weaviate B.V.

Initial release

2014

1993

2009

2020

2019

Current release

3.4-12

3.14.1, January 2024

0.5, April 2021

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPL V3

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++

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

with some exceptions

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

integer and binary

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

via Elasticsearch

yes

with tags

yes

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

SQL

Support of SQL

SQL-like query language

GraphQL is used as query language

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

Proprietary protocol
Thrift

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

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

C++

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

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

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

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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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