DBMS > Apache Pinot vs. CrateDB vs. GBase vs. Postgres-XL

System Properties Comparison Apache Pinot vs. CrateDB vs. GBase 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

Distributed Database based on Lucene

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

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

Primary database model

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

Technical documentation

docs.pinot.apache.org

cratedb.com/docs

www.postgres-xl.org/documentation

Developer

Apache Software Foundation and contributors

Crate

General Data Technology Co., Ltd.

Initial release

2015

2013

2004

2014

since 2012, originally named StormDB

Current release

1.0.0, September 2023

5.8.1, August 2024

GBase 8a, GBase 8s, GBase 8c

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

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

C, Java, Python

Server operating systems

All OS with a Java JDK11 or higher

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux

Linux
macOS

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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

SQL

Support of SQL

SQL-like query language

yes, but no triggers and constraints, and PostgreSQL compatibility

Standard with numerous extensions

yes

distributed, parallel query execution

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

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

Supported programming languages

Go
Java
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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.

User concepts

Access control

rights management via user accounts

yes

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

Pinot for Low-Latency Offline Table Analytics
29 August 2024, Uber

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

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

StarTree Makes Observability Case for Apache Pinot Database
8 May 2024, DevOps.com

provided by Google News

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

Taleo Consulting and CrateDB Announce Strategic Partnership to Transform Data Management and Analytics in Financial Services markets
29 July 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

provided by Google News

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