DBMS > Adabas vs. Couchbase vs. CrateDB vs. GraphDB vs. Oracle Coherence

System Properties Comparison Adabas vs. Couchbase vs. CrateDB vs. GraphDB vs. Oracle Coherence

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed Database based on Lucene

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Oracles in-memory data grid solution

Primary database model

Multivalue DBMS

Document store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
RDF store

Key-value store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

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

www.couchbase.com

cratedb.com

www.ontotext.com

www.oracle.com/java/coherence

Technical documentation

docs.couchbase.com

cratedb.com/docs

graphdb.ontotext.com/documentation

docs.oracle.com/en/middleware/standalone/coherence

Social network pages

Developer

Software AG

Couchbase, Inc.

Crate

Ontotext

Oracle

Initial release

1971

2011

2013

2000

2007

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

10.4, October 2023

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

C, C++, Go and Erlang

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

All OS with a Java VM
Linux
OS X
Windows

All OS with a Java VM

Data scheme

yes

schema-free

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

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

Typing

predefined data types such as float or date

yes

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

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes, but no triggers and constraints, and PostgreSQL compatibility

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

JCache
JPA
RESTful HTTP API

Supported programming languages

Natural

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.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
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

in Natural

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions (Javascript)

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

via the TAP protocol

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

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

Automatic Sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

including cross data center replication
Source-replica replication

Configurable replication on table/partition-level

Multi-source replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

Transaction concepts

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

ACID

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

rights management via user accounts

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Metadata enrichment and management, linked data publishing, semantic inferencing...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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GraphDB provides a platform for building next-generation AI and Knowledge Graph...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
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Licensing and pricing models

See CrateDB pricing >
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GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.