DBMS > Apache Drill vs. EsgynDB vs. Greenplum vs. H2GIS vs. Heroic

System Properties Comparison Apache Drill vs. EsgynDB vs. Greenplum vs. H2GIS vs. Heroic

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Spatial extension of H2

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Document store
Relational DBMS

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Website

github.com/spotify/heroic

Technical documentation

drill.apache.org/docs

docs.greenplum.org

www.h2gis.org/docs/home

spotify.github.io/heroic

Developer

Apache Software Foundation

Esgyn

Pivotal Software Inc.

CNRS

Spotify

Initial release

2012

2015

2005

2013

2014

Current release

1.20.3, January 2023

7.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Open Source

LGPL 3.0

Open Source

Apache 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

Server operating systems

Linux
OS X
Windows

Linux

Data scheme

schema-free

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

since Version 4.2

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

Java

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes

based on H2

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

yes

based on H2

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, businesswire.com

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

Chapter 1. Introducing the Greenplum Database
6 December 2018, O'Reilly Media

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale
9 September 2019, AWS Blog

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

EMC Introduces Breakthrough 'Big Data' Computing System
13 October 2010, PR Newswire

provided by Google News

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