DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Pinot vs. ClickHouse vs. JanusGraph

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Pinot vs. ClickHouse vs. JanusGraph

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

pinot.apache.org

clickhouse.com

janusgraph.org

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.pinot.apache.org

clickhouse.com/docs

docs.janusgraph.org

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation and contributors

Clickhouse Inc.

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2016

2015

2016

2017

Current release

1.0.0, September 2023

v24.4.1.2088-stable, May 2024

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

Java

C++

Java

Server operating systems

hosted

All OS with a Java JDK11 or higher

FreeBSD
Linux
macOS

Linux
OS X
Unix
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

JDBC
ODBC

JDBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
Java
Perl
Python
R

Go
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

key based and custom

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

User authentification and security via Rexster Graph Server

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