DBMS > Adabas vs. FatDB vs. Google BigQuery vs. PouchDB vs. Yaacomo

System Properties Comparison Adabas vs. FatDB vs. Google BigQuery vs. PouchDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Large scale data warehouse service with append-only tables

JavaScript DBMS with an API inspired by CouchDB

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

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

cloud.google.com/bigquery

pouchdb.com

yaacomo.com

Technical documentation

cloud.google.com/bigquery/docs

pouchdb.com/guides

Developer

Software AG

FatCloud

Google

Apache Software Foundation

Q2WEB GmbH

Initial release

1971

2012

2010

2012

2009

Current release

7.1.1, June 2019

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

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Windows

hosted

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

Android
Linux
Windows

Data scheme

yes

schema-free

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

via views

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Via inetgration in SQL Server

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

in Natural

yes

via applications

user defined functions

in JavaScript

View functions in JavaScript

Triggers

yes

via applications

yes

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

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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)

Can implement custom security layer via applications

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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