DBMS > Apache Pinot vs. Faircom DB vs. GBase vs. GreptimeDB vs. SWC-DB

System Properties Comparison Apache Pinot vs. Faircom DB vs. GBase vs. GreptimeDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

pinot.apache.org

www.faircom.com/products/faircom-db

www.gbase.cn

greptime.com

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

Technical documentation

docs.pinot.apache.org

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.greptime.com

Developer

Apache Software Foundation and contributors

FairCom Corporation

General Data Technology Co., Ltd.

Greptime Inc.

Alex Kashirin

Initial release

2015

1979

2004

2022

2020

Current release

1.0.0, September 2023

V12, November 2020

GBase 8a, GBase 8s, GBase 8c

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

Open Source

Apache Version 2.0

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

Java

ANSI C, C++

C, Java, Python

Rust

C++

Server operating systems

All OS with a Java JDK11 or higher

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

schema free, schema optional, schema required, partial schema,

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

SQL-like query language

yes, ANSI SQL with proprietary extensions

Standard with numerous extensions

yes

SQL-like query language

APIs and other access methods

JDBC

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
C API
JDBC
ODBC

gRPC
HTTP API
JDBC

Proprietary protocol
Thrift

Supported programming languages

Go
Java
Python

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C++
Erlang
Go
Java
JavaScript

C++

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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 with additional protections for files

yes

Simple rights management via user accounts

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

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More resources

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