DBMS > GreptimeDB vs. IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. UniData,UniVerse

System Properties Comparison GreptimeDB vs. IBM Db2 Event Store vs. mSQL vs. OrigoDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Multivalue DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

greptime.com

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

hughestech.com.au/products/msql

origodb.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.greptime.com

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

origodb.com/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Greptime Inc.

IBM

Hughes Technologies

Robert Friberg et al

Rocket Software

Initial release

2022

2017

1994

2009

under the name LiveDB

1985

Current release

2.0

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

commercial

free licenses can be provided

Open Source

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

C and C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

optional

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

gRPC
HTTP API
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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
C++
Delphi
Java
Perl
PHP
Tcl

.Net

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Domain Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

configurable

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

Write ahead log

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Role based authorization

Access rights according to SQL-standard and operating system based

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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