DBMS > Badger vs. GBase vs. Hyprcubd vs. OpenQM vs. Weaviate

System Properties Comparison Badger vs. GBase vs. Hyprcubd vs. OpenQM vs. Weaviate

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Serverless Time Series DBMS

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

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

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

github.com/dgraph-io/badger

www.gbase.cn

hyprcubd.com (offline)

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

github.com/weaviate/weaviate
weaviate.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

weaviate.io/developers/weaviate

Developer

DGraph Labs

General Data Technology Co., Ltd.

Hyprcubd, Inc.

Rocket Software, originally Martin Phillips

Weaviate B.V.

Initial release

2017

2004

1993

2019

Current release

GBase 8a, GBase 8s, GBase 8c

3.4-12

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

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

C, Java, Python

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

schema-free

yes

with some exceptions

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

Standard with numerous extensions

SQL-like query language

GraphQL is used as query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

gRPC (https)

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

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

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

token access

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...
» more

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.

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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