DBMS > Adabas vs. Heroic vs. Microsoft Azure AI Search vs. OrigoDB vs. TerarkDB

System Properties Comparison Adabas vs. Heroic vs. Microsoft Azure AI Search vs. OrigoDB vs. TerarkDB

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

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

Search-as-a-service for web and mobile app development

A fully ACID in-memory object graph database

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Multivalue DBMS

Time Series DBMS

Search engine

Document store
Object oriented DBMS

Key-value store

Secondary database models

Vector DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

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

github.com/spotify/heroic

azure.microsoft.com/en-us/services/search

origodb.com

github.com/bytedance/terarkdb

Technical documentation

spotify.github.io/heroic

learn.microsoft.com/en-us/azure/search

origodb.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Software AG

Spotify

Microsoft

Robert Friberg et al

ByteDance, originally Terark

Initial release

1971

2014

2015

2009

under the name LiveDB

2016

Current release

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

commercial

restricted open source version available

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

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

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

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

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

RESTful HTTP API

.NET Client API
HTTP API
LINQ

C++ API
Java API

Supported programming languages

Natural

C#
Java
JavaScript
Python

.Net

C++
Java

Server-side scripts

Stored procedures

in Natural

yes

Triggers

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

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Implicit feature of the cloud service

Source-replica replication

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

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)

yes

using Azure authentication

Role based authorization

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