DBMS > Adabas vs. Google Cloud Bigtable vs. Ingres vs. Riak TS vs. searchxml

System Properties Comparison Adabas vs. Google Cloud Bigtable vs. Ingres vs. Riak TS vs. searchxml

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Well established RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Multivalue DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

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

cloud.google.com/bigtable

www.actian.com/databases/ingres

www.searchxml.net/category/products

Technical documentation

cloud.google.com/bigtable/docs

docs.actian.com/ingres

www.tiot.jp/riak-docs/riak/ts/latest

www.searchxml.net/support/handouts

Developer

Software AG

Google

Actian Corporation

Open Source, formerly Basho Technologies

informationpartners gmbh

Initial release

1971

2015

1974

originally developed at University Berkely in early 1970s

2015

Current release

11.2, May 2022

3.0.0, September 2022

1.0

License

Commercial or Open Source

commercial

Open Source

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

Erlang

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X

Windows

Data scheme

yes

schema-free

yes

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

yes, limited

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Natural

C#
C++
Go
Java
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

in Natural

yes

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Internal replication in Colossus, and regional replication between two clusters in different zones

Ingres Replicator

selectable replication factor

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Atomic single-row operations

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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.

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)

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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