DBMS > Adabas vs. Hive vs. Ignite vs. RocksDB vs. Teradata

System Properties Comparison Adabas vs. Hive vs. Ignite vs. RocksDB vs. Teradata

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial 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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

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

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

github.com/facebook/rocksdb/wiki

docs.teradata.com

Developer

Software AG

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Facebook, Inc.

Teradata

Initial release

1971

2012

2015

2013

1984

Current release

3.1.3, April 2022

Apache Ignite 2.6

9.2.1, May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Java, .Net

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

hosted
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

SQL 2016 + 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
ODBC
Thrift

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

C++ API
Java API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Natural

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

yes (compute grid and cache interceptors can be used instead)

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes (cache interceptors and events)

yes

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

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

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.

yes

User concepts

Access control

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

Access rights for users, groups and roles

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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