DBMS > Adabas vs. BigObject vs. EsgynDB vs. RDF4J vs. Weaviate

System Properties Comparison Adabas vs. BigObject vs. EsgynDB vs. RDF4J vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Analytic DBMS for real-time computations and queries

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Multivalue DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

RDF store

Vector DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

bigobject.io

www.esgyn.cn

rdf4j.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.bigobject.io

rdf4j.org/documentation

weaviate.io/developers/weaviate

Developer

Software AG

BigObject, Inc.

Esgyn

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

Weaviate B.V.

Initial release

1971

2015

2004

2019

Current release

1.19, May 2023

License

Commercial or Open Source

commercial

free community edition available

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

C++, Java

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

GraphQL is used as query language

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

Natural

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

in Natural

Lua

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

Multi-source replication between multi datacenters

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

fine grained access rights according to SQL-standard

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...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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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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