DBMS > Adabas vs. AlaSQL vs. Google Cloud Datastore vs. KairosDB vs. Oracle

System Properties Comparison Adabas vs. AlaSQL vs. Google Cloud Datastore vs. KairosDB vs. Oracle

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

JavaScript DBMS library

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

Distributed Time Series DBMS based on Cassandra or H2

Widely used RDBMS

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

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

alasql.org

cloud.google.com/datastore

github.com/kairosdb/kairosdb

www.oracle.com/database

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/datastore/docs

kairosdb.github.io

docs.oracle.com/en/database

Developer

Software AG

Andrey Gershun & Mathias R. Wulff

Google

Oracle

Initial release

1971

2014

2008

2013

1980

Current release

1.2.2, November 2018

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

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

JavaScript

Java

C and C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

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

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language (GQL)

yes

with proprietary extensions

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JavaScript API

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

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Natural

JavaScript

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

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

in Natural

using Google App Engine

PL/SQL

also stored procedures in Java possible

Triggers

yes

Callbacks using the Google Apps Engine

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

based on Cassandra

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

Multi-source replication using Paxos

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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.

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

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

simple password-based access control

fine grained access rights according to SQL-standard

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