DBMS > Apache Impala vs. EsgynDB vs. GeoMesa vs. gStore

System Properties Comparison Apache Impala vs. EsgynDB vs. GeoMesa vs. gStore

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A native Graph DBMS to store and maintain very large RDF datasets.

Primary database model

Relational DBMS

Spatial DBMS

Graph DBMS
RDF store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Website

Technical documentation

impala.apache.org/impala-docs.html

www.geomesa.org/documentation/stable/user/index.html

en.gstore.cn/#/enDocs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Esgyn

CCRi and others

Initial release

2013

2015

2014

2016

Current release

4.1.0, June 2022

5.0.0, May 2024

1.2, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache License 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

Scala

C++

Server operating systems

Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP API
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

depending on storage layer

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

depending on storage layer

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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27 October 2017, KDnuggets

provided by Google News

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