DBMS > FatDB vs. GreptimeDB vs. Hazelcast vs. MySQL vs. SWC-DB

System Properties Comparison FatDB vs. GreptimeDB vs. Hazelcast vs. MySQL vs. SWC-DB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

A widely adopted in-memory data grid

Widely used open source RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

greptime.com

hazelcast.com

www.mysql.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.greptime.com

hazelcast.org/imdg/docs

dev.mysql.com/doc

Developer

FatCloud

Greptime Inc.

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

Alex Kashirin

Initial release

2012

2022

2008

1995

2020

Current release

5.3.6, November 2023

9.0.0, July 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

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

Java

C and C++

C++

Server operating systems

Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

schema-free

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL-like query language

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC
HTTP API
JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C++

Server-side scripts

Stored procedures

yes

via applications

Python

yes

Event Listeners, Executor Services

yes

proprietary syntax

Triggers

yes

via applications

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Replicated Map

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Can implement custom security layer via applications

Simple rights management via user accounts

Role-based access control

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...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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Key customers

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