DBMS > Adabas vs. GreptimeDB vs. RRDtool vs. Transwarp ArgoDB vs. Transwarp Hippo

System Properties Comparison Adabas vs. GreptimeDB vs. RRDtool vs. Transwarp ArgoDB vs. Transwarp Hippo

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Search engine

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	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

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

greptime.com

oss.oetiker.ch/rrdtool

www.transwarp.cn/en/product/argodb

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.greptime.com

oss.oetiker.ch/rrdtool/doc

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Software AG

Greptime Inc.

Tobias Oetiker

Transwarp

Initial release

1971

2022

1999

2023

Current release

1.8.0, 2022

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Android
Docker
FreeBSD
Linux
macOS
Windows

HP-UX
Linux

Linux
macOS

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

Vector, Numeric and String

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.

Exporting into and restoring from XML files possible

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

gRPC
HTTP API
JDBC

in-process shared library
Pipes

RESTful HTTP API

Supported programming languages

Natural

C++
Erlang
Go
Java
JavaScript

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

in Natural

Python

Triggers

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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)

Simple rights management via user accounts

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Typical application scenarios

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

Key customers

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

Market metrics

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

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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