DBMS > Axibase vs. Dragonfly vs. RDF4J vs. Weaviate

System Properties Comparison Axibase vs. Dragonfly vs. RDF4J vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

axibase.com/docs/atsd/finance

github.com/dragonflydb/dragonfly
www.dragonflydb.io

rdf4j.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.dragonflydb.io/docs

rdf4j.org/documentation

weaviate.io/developers/weaviate

Developer

Axibase Corporation

DragonflyDB team and community contributors

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

Weaviate B.V.

Initial release

2013

2023

2004

2019

Current release

15585

1.0, March 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

BSL 1.1

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

C++

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

scheme-free

yes

RDF Schemas

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

strings, hashes, lists, sets, sorted sets, bit arrays

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.

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

GraphQL is used as query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

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

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Lua

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

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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