DBMS > Adabas vs. Apache Phoenix vs. Google BigQuery vs. Graphite vs. HyperSQL

System Properties Comparison Adabas vs. Apache Phoenix vs. Google BigQuery vs. Graphite vs. HyperSQL

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

Large scale data warehouse service with append-only tables

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Website

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

phoenix.apache.org

cloud.google.com/bigquery

github.com/graphite-project/graphite-web

hsqldb.org

Technical documentation

phoenix.apache.org

cloud.google.com/bigquery/docs

graphite.readthedocs.io

hsqldb.org/web/hsqlDocsFrame.html

Developer

Software AG

Apache Software Foundation

Google

Chris Davis

Initial release

1971

2014

2010

2006

2001

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

based on BSD license

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

Python

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Unix
Windows

hosted

Linux
Unix

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

JDBC

RESTful HTTP/JSON API

HTTP API
Sockets

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Natural

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

Java, SQL

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

none

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

locking

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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