DBMS > EsgynDB vs. H2GIS vs. LeanXcale vs. Sadas Engine vs. StarRocks

System Properties Comparison EsgynDB vs. H2GIS vs. LeanXcale vs. Sadas Engine vs. StarRocks

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial extension of H2

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Relational DBMS

Spatial DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

Technical documentation

www.h2gis.org/docs/home

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Esgyn

CNRS

LeanXcale

SADAS s.r.l.

The Linux Foundation

since Feb 2023

Initial release

2015

2013

2015

2006

2020

Current release

8.0

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

commercial

free trial version available

Open Source

Apache Version 2.0

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

C++, Java

Java

C++

C++, Java

Server operating systems

Linux

AIX
Linux
Windows

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
Proprietary protocol

JDBC
MySQL protocol

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

C
Java
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

based on H2

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

based on H2

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

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