DBMS > Adabas vs. Axibase vs. Derby vs. Google Cloud Datastore vs. Stardog

System Properties Comparison Adabas vs. Axibase vs. Derby vs. Google Cloud Datastore vs. Stardog

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

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	5.30
Rank	#66	Overall
	#36	Relational DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

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

axibase.com/docs/atsd/finance

db.apache.org/derby

cloud.google.com/datastore

www.stardog.com

Technical documentation

db.apache.org/derby/manuals/index.html

cloud.google.com/datastore/docs

docs.stardog.com

Developer

Software AG

Axibase Corporation

Apache Software Foundation

Google

Stardog-Union

Initial release

1971

2013

1997

2008

2010

Current release

15585

10.17.1.0, November 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

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

Open Source

Apache version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

All OS with a Java VM

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

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

yes

yes, details here

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.

yes

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

yes

SQL-like query language (GQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Natural

Go
Java
PHP
Python
R
Ruby

Java

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

in Natural

yes

Java Stored Procedures

using Google App Engine

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Callbacks using the Google Apps Engine

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

Multi-source replication using Paxos

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

relationships in graphs

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

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