DBMS > Adabas vs. GreptimeDB vs. IBM Db2 Event Store vs. Kinetica vs. Snowflake

System Properties Comparison Adabas vs. GreptimeDB vs. IBM Db2 Event Store vs. Kinetica vs. Snowflake

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

Distributed Event Store optimized for Internet of Things use cases

Fully vectorized database across both GPUs and CPUs

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Multivalue DBMS

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

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

greptime.com

www.ibm.com/products/db2-event-store

www.kinetica.com

www.snowflake.com

Technical documentation

docs.greptime.com

www.ibm.com/docs/en/db2-event-store

docs.kinetica.com

docs.snowflake.net/manuals/index.html

Developer

Software AG

Greptime Inc.

IBM

Kinetica

Snowflake Computing Inc.

Initial release

1971

2022

2017

2012

2014

Current release

2.0

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C and C++

C, C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

hosted

Data scheme

yes

schema-free, schema definition possible

yes

support of semi-structured data formats (JSON, XML, Avro)

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

through the embedded Spark runtime

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

gRPC
HTTP API
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Natural

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

Python

yes

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Active-active shard replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Users with fine-grained authorization concept, user roles and pluggable authentication

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...
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Licensing and pricing models

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