DBMS > Apache Phoenix vs. Apache Pinot vs. GeoSpock vs. Snowflake

System Properties Comparison Apache Phoenix vs. Apache Pinot vs. GeoSpock vs. Snowflake

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Spatial and temporal data processing engine for extreme data scale

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

phoenix.apache.org

pinot.apache.org

geospock.com

www.snowflake.com

Technical documentation

phoenix.apache.org

docs.pinot.apache.org

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache Software Foundation and contributors

GeoSpock

Snowflake Computing Inc.

Initial release

2014

2015

2014

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.0.0, September 2023

2.0, September 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Javascript

Server operating systems

Linux
Unix
Windows

All OS with a Java JDK11 or higher

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

yes

SQL-like query language

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Go
Java
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Automatic sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users can be defined per table

Users with fine-grained authorization concept, user roles and pluggable authentication

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