DBMS > Apache Pinot vs. Galaxybase vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison Apache Pinot vs. Galaxybase vs. Microsoft Azure Data Explorer vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, ACID-compliant native distributed parallel graph platform

Fully managed big data interactive analytics platform

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

column oriented

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.50
Rank	#248	Overall
	#117	Relational DBMS

Score	0.00
Rank	#385	Overall
	#41	Graph DBMS

Score	3.00
Rank	#86	Overall
	#47	Relational DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

pinot.apache.org

galaxybase.com

azure.microsoft.com/services/data-explorer

www.postgresql.org

Technical documentation

docs.pinot.apache.org

docs.microsoft.com/en-us/azure/data-explorer

www.postgresql.org/docs

Developer

Apache Software Foundation and contributors

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Microsoft

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2017

2019

1989

1989: Postgres, 1996: PostgreSQL

Current release

1.0.0, September 2023

Nov 20, November 2021

cloud service with continuous releases

16.4, August 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

C and Java

Server operating systems

All OS with a Java JDK11 or higher

Linux

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

Strong typed schema

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

standard with numerous extensions

APIs and other access methods

JDBC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

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

Supported programming languages

Go
Java
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined procedures and functions

Yes, possible languages: KQL, Python, R

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

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

Role-based access control

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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