DBMS > Adabas vs. Hive vs. Riak KV vs. SAP HANA vs. Vertica

System Properties Comparison Adabas vs. Hive vs. Riak KV vs. SAP HANA vs. Vertica

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

Distributed, fault tolerant key-value store

In-memory, column based data store. Available as appliance or cloud service

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial 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	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

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

hive.apache.org

www.sap.com/products/hana.html

www.vertica.com

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/hana

vertica.com/documentation

Developer

Software AG

Apache Software Foundation

initially developed by Facebook

OpenSource, formerly Basho Technologies

SAP

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1971

2012

2009

2010

2005

Current release

3.1.3, April 2022

3.2.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache version 2, commercial enterprise edition

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

also available as a cloud based service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Erlang

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

Linux
OS X

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

Secondary indexes

yes

restricted

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

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

HTTP API
Native Erlang Interface

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Natural

C++
Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

Erlang

SQLScript, R

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

pre-commit hooks and post-commit hooks

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

no "single point of failure"

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

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

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

yes, using Riak Security

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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