DBMS > Adabas vs. Amazon Neptune vs. Couchbase vs. HugeGraph vs. Kinetica

System Properties Comparison Adabas vs. Amazon Neptune vs. Couchbase vs. HugeGraph vs. Kinetica

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

Fast, reliable graph database built for the cloud

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

A fast-speed and highly-scalable Graph DBMS

Fully vectorized database across both GPUs and CPUs

Primary database model

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

Spatial DBMS
Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

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

aws.amazon.com/neptune

www.couchbase.com

github.com/hugegraph
hugegraph.apache.org

www.kinetica.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.couchbase.com

hugegraph.apache.org/docs

docs.kinetica.com

Developer

Software AG

Amazon

Couchbase, Inc.

Baidu

Kinetica

Initial release

1971

2017

2011

2018

2012

Current release

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

0.9

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Apache Version 2.0

commercial

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.

Implementation language

C, C++, Go and Erlang

Java

C, C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Windows

Linux
macOS
Unix

Linux

Data scheme

yes

schema-free

yes

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

also supports composite index and range index

yes

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

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Natural

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Groovy
Java
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

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

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

via the TAP protocol

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

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

none

Automatic Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication

including cross data center replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

GPU vRAM or System RAM

User concepts

Access control

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Users, roles and permissions

Access rights for users and roles on table level

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