DBMS > AgensGraph vs. ClickHouse vs. EDB Postgres vs. LeanXcale vs. Microsoft Azure Table Storage

System Properties Comparison AgensGraph vs. ClickHouse vs. EDB Postgres vs. LeanXcale vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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.

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

bitnine.net/agensgraph

clickhouse.com

www.enterprisedb.com

www.leanxcale.com

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

bitnine.net/documentation

clickhouse.com/docs

www.enterprisedb.com/docs

Developer

Bitnine Global Inc.

Clickhouse Inc.

EnterpriseDB

LeanXcale

Microsoft

Initial release

2016

2005

2015

2012

Current release

2.1, December 2018

v24.4.1.2088-stable, May 2024

14, December 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

commercial

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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Implementation language

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux
Windows

hosted

Data scheme

depending on used data model

yes

schema-free

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

yes

standard with numerous extensions

yes

through Apache Derby

APIs and other access methods

Cypher Query Language
JDBC

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

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

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
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

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C
Java
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

key based and custom

horizontal partitioning

by hash, list or range

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Multi-source replication

yes

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

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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.

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

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