DBMS > Badger vs. Hyprcubd vs. MySQL vs. SQLite vs. Weaviate

System Properties Comparison Badger vs. Hyprcubd vs. MySQL vs. SQLite 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.

Serverless Time Series DBMS

Widely used open source RDBMS

Widely used embeddable, in-process RDBMS

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

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

github.com/dgraph-io/badger

hyprcubd.com (offline)

www.mysql.com

www.sqlite.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

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

dev.mysql.com/doc

www.sqlite.org/docs.html

weaviate.io/developers/weaviate

Developer

DGraph Labs

Hyprcubd, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Dwayne Richard Hipp

Weaviate B.V.

Initial release

2017

1995

2000

2019

Current release

8.4.0, April 2024

3.45.3 (15 April 2024), April 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Public Domain

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language

yes

with proprietary extensions

yes

SQL-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

gRPC (https)

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

via file-system locks

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

token access

Users with fine-grained authorization concept

no user groups or roles

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.