DBMS > IBM Db2 Event Store vs. openGemini vs. OpenTSDB vs. TerarkDB

System Properties Comparison IBM Db2 Event Store vs. openGemini vs. OpenTSDB vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Scalable Time Series DBMS based on HBase

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Key-value store

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

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

www.opengemini.org
github.com/openGemini

opentsdb.net

github.com/bytedance/terarkdb

Technical documentation

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

docs.opengemini.org/guide

opentsdb.net/docs/build/html/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

IBM

Huawei and openGemini community

currently maintained by Yahoo and other contributors

ByteDance, originally Terark

Initial release

2017

2022

2011

2016

Current release

2.0

1.1, July 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache Version 2.0

Open Source

LGPL

commercial

restricted open source version available

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

C and C++

Java

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

numeric data for metrics, strings for tags

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

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP REST

HTTP API
Telnet API

C++ API
Java API

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Erlang
Go
Java
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

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

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators and common users accounts

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More resources

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