DBMS > CrateDB vs. jBASE vs. RDF4J vs. Weaviate

System Properties Comparison CrateDB vs. jBASE vs. RDF4J vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

A robust multi-value DBMS comprising development tools and middleware

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Multivalue DBMS

RDF store

Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

cratedb.com

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

rdf4j.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

cratedb.com/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

rdf4j.org/documentation

weaviate.io/developers/weaviate

Developer

Crate

Rocket Software (formerly Zumasys)

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Weaviate B.V.

Initial release

2013

1991

2004

2019

Current release

5.8.1, August 2024

5.7

1.19, May 2023

License

Commercial or Open Source

Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

RDF Schemas

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

optional

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, but no triggers and constraints, and PostgreSQL compatibility

Embedded SQL for jBASE in BASIC

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
Basic
Jabbascript
Java

Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

rights management via user accounts

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,...
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Competitive advantages

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