DBMS > Adabas vs. GreptimeDB vs. GridDB vs. MySQL

System Properties Comparison Adabas vs. GreptimeDB vs. GridDB vs. MySQL

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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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Scalable in-memory time series database optimized for IoT and Big Data

Widely used open source RDBMS

Primary database model

Multivalue DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

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

greptime.com

griddb.net

www.mysql.com

Technical documentation

docs.greptime.com

docs.griddb.net

dev.mysql.com/doc

Developer

Software AG

Greptime Inc.

Toshiba Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

1971

2022

2013

1995

Current release

5.1, August 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++

C and C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

with proprietary 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

gRPC
HTTP API
JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Natural

C++
Erlang
Go
Java
JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

in Natural

Python

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at container level

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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)

Simple rights management via user accounts

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

GitHub trending repository
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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