DBMS > Apache Impala vs. H2GIS vs. PieCloudDB vs. Postgres-XL vs. Realm

System Properties Comparison Apache Impala vs. H2GIS vs. PieCloudDB vs. Postgres-XL vs. Realm

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Spatial extension of H2

A cloud-native analytic database platform with new technologoy for elastic MPP

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Secondary database models

Document store

Relational DBMS

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

www.postgres-xl.org/documentation

realm.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

OpenPie

Realm, acquired by MongoDB in May 2019

Initial release

2013

2014

since 2012, originally named StormDB

2014

Current release

4.1.0, June 2022

2.1, January 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

commercial

Open Source

Mozilla public license

Open Source

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.

Implementation language

C++

Java

Server operating systems

Linux

hosted

Linux
macOS

Android
Backend: server-less
iOS
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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

CLI Client
JDBC
ODBC

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

Supported programming languages

All languages supporting JDBC/ODBC

Java

Java
PL/SQL
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

user defined functions

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

User Roles and pluggable authentication with full SQL Standard

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

PieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more

Competitive advantages

Extreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more

Typical application scenarios

PieCloudDB is ideal for Data mining applications that require extreme scalability...
» more

Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
» more

Licensing and pricing models

PieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment；...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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

provided by Google News

MongoDB aims to unify developer experience with launch of MongoDB Cloud
9 June 2020, diginomica

Danish CEO explains Silicon Valley learning curve for European entrepreneurs - San Francisco Business Times
6 October 2016, The Business Journals

Is Swift the Future of Server-side Development?
12 September 2017, Solutions Review

Kotlin Programming Language Will Surpass Java On Android Next Year
15 October 2017, Fossbytes

Java Synthetic Methods — What are these? | by Vaibhav Singh
27 February 2021, DataDrivenInvestor

provided by Google News

Share this page