DBMS > Adabas vs. Google BigQuery vs. H2GIS vs. Hive vs. OceanBase

System Properties Comparison Adabas vs. Google BigQuery vs. H2GIS vs. Hive vs. OceanBase

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

Large scale data warehouse service with append-only tables

Spatial extension of H2

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

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Secondary database models

Relational DBMS

Document store
Wide column store

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Trend Chart

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

Website

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

cloud.google.com/bigquery

www.h2gis.org

hive.apache.org

en.oceanbase.com

Technical documentation

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

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

en.oceanbase.com/docs/oceanbase-database

Developer

Software AG

Google

CNRS

Apache Software Foundation

initially developed by Facebook

OceanBase

previously Alibaba and Ant Group

Initial release

1971

2010

2013

2012

2010

Current release

3.1.3, April 2022

4.3.0, April 2024

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

Apache Version 2

Open Source

Commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

All OS with a Java VM

Linux

Data scheme

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

C++
Java
PHP
Python

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

yes

based on H2

yes

user defined functions and integration of map-reduce

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

based on H2

selectable replication factor

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

based on H2

Access rights for users, groups and roles

Access rights for users, groups and roles according to SQL-standard

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