DBMS > Adabas vs. Blueflood vs. Dolt vs. Faircom EDGE vs. Lovefield

System Properties Comparison Adabas vs. Blueflood vs. Dolt vs. Faircom EDGE vs. Lovefield

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 Cassandra

A MySQL compatible DBMS with Git-like versioning of data and schema

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Multivalue DBMS

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

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

blueflood.io

github.com/dolthub/dolt
www.dolthub.com

www.faircom.com/products/faircom-edge

google.github.io/lovefield

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.dolthub.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

Developer

Software AG

Rackspace

DoltHub Inc

FairCom Corporation

Google

Initial release

1971

2013

2018

1979

2014

Current release

V3, October 2020

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Apache 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

ANSI C, C++

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X

Linux
macOS
Windows

Android
Linux

ARM, x86
Raspbian
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

predefined scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

yes

ANSI SQL queries

SQL-like query language

via JavaScript builder pattern

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

CLI Client
HTTP REST

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Natural

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript

Server-side scripts

Stored procedures

in Natural

yes

currently in alpha release

yes

.Net, JavaScript, C/C++

Triggers

yes

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

none

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

based on Cassandra

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

Synchronous and asynchronous realtime replication based on transaction logs

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

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

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)

Only one user is configurable, and must be specified in the config file at startup

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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