DBMS > Apache Pinot vs. GreptimeDB vs. Infobright vs. Postgres-XL

System Properties Comparison Apache Pinot vs. GreptimeDB vs. Infobright vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

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

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

pinot.apache.org

greptime.com

ignitetech.com/softwarelibrary/infobrightdb

www.postgres-xl.org

Technical documentation

docs.pinot.apache.org

docs.greptime.com

www.postgres-xl.org/documentation

Developer

Apache Software Foundation and contributors

Greptime Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2015

2022

2005

2014

since 2012, originally named StormDB

Current release

1.0.0, September 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Mozilla public license

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

Rust

Server operating systems

All OS with a Java JDK11 or higher

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free, schema definition possible

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC

gRPC
HTTP API
JDBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Go
Java
Python

C++
Erlang
Go
Java
JavaScript

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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

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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

Recent citations in the news

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

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