DBMS > Adabas vs. Blueflood vs. FatDB vs. Lovefield vs. NSDb

System Properties Comparison Adabas vs. Blueflood vs. FatDB vs. Lovefield vs. NSDb

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.

Description

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

used typically together with the Natural programming platform

Scalable TimeSeries DBMS based on Cassandra

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

Embeddable relational database for web apps written in pure JavaScript

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Multivalue DBMS

Time Series DBMS

Document store
Key-value store

Relational 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	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

blueflood.io

google.github.io/lovefield

nsdb.io

Technical documentation

github.com/rax-maas/blueflood/wiki

github.com/google/lovefield/blob/master/docs/spec_index.md

nsdb.io/Architecture

Developer

Software AG

Rackspace

FatCloud

Google

Initial release

1971

2013

2012

2014

2017

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Java, Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X

Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Data scheme

yes

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Via inetgration in SQL Server

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

HTTP REST

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

gRPC
HTTP REST
WebSocket

Supported programming languages

Natural

JavaScript

Java
Scala

Server-side scripts

Stored procedures

in Natural

yes

via applications

Triggers

yes

via applications

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

based on Cassandra

selectable replication factor

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

Using Apache Lucene

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

Can implement custom security layer via applications

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More resources

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