DBMS > Adabas vs. Drizzle vs. Heroic vs. OrigoDB

System Properties Comparison Adabas vs. Drizzle vs. Heroic vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

used typically together with the Natural programming platform

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A fully ACID in-memory object graph database

Primary database model

Multivalue DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Website

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

github.com/spotify/heroic

origodb.com

Technical documentation

spotify.github.io/heroic

origodb.com/docs

Developer

Software AG

Drizzle project, originally started by Brian Aker

Spotify

Robert Friberg et al

Initial release

1971

2008

2014

2009

under the name LiveDB

Current release

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

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

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

FreeBSD
Linux
OS X

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
HTTP API
LINQ

Supported programming languages

Natural

C
C++
Java
PHP

.Net

Server-side scripts

Stored procedures

in Natural

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Domain Events

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

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role based authorization

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More resources

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