DBMS > Adabas vs. Axibase vs. GeoSpock vs. Hypertable vs. Microsoft Azure Cosmos DB

System Properties Comparison Adabas vs. Axibase vs. GeoSpock vs. Hypertable vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Hypertable has stopped its further development with March 2016 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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Spatial and temporal data processing engine for extreme data scale

An open source BigTable implementation based on distributed file systems such as Hadoop

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

axibase.com/docs/atsd/finance

geospock.com

azure.microsoft.com/services/cosmos-db

Technical documentation

learn.microsoft.com/azure/cosmos-db

Developer

Software AG

Axibase Corporation

GeoSpock

Hypertable Inc.

Microsoft

Initial release

1971

2013

2009

2014

Current release

15585

2.0, September 2019

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

GNU version 3. Commercial license available

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

Java

Java, Javascript

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

JSON types

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

temporal, categorical

restricted

only exact value or prefix value scans

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

ANSI SQL for query only (using Presto)

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

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

C++ API
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Natural

Go
Java
PHP
Python
R
Ruby

C++
Java
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

in Natural

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Automatic sharding

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

selectable replication factor on file system level

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

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

Access rights for users can be defined per table

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.