DBMS > Apache Impala vs. CouchDB vs. FeatureBase vs. H2GIS

System Properties Comparison Apache Impala vs. CouchDB vs. FeatureBase vs. H2GIS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Spatial extension of H2

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

Relational DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

docs.featurebase.com

www.h2gis.org/docs/home

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Molecula and Pilosa Open Source Contributors

CNRS

Initial release

2013

2005

2017

2013

Current release

4.1.0, June 2022

3.3.3, December 2023

2022, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

Open Source

LGPL 3.0

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++

Erlang

Java

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

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

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL queries

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

gRPC
JDBC
Kafka Connector
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Java
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

based on H2

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

yes

based on H2

More information provided by the system vendor

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

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

show all

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

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

How to install the CouchDB NoSQL database on Debian Server 11
16 June 2022, TechRepublic

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

CouchDB 3.0 ends admin party era • DEVCLASS
27 February 2020, DevClass

Tracking Expenses with CouchDB and Angular — SitePoint
28 August 2014, SitePoint

How to Connect Your Flask App With CouchDB: A NoSQL Database - MUO
14 August 2021, MakeUseOf

provided by Google News

The 10 Hottest Big Data Startups Of 2021
18 November 2021, CRN

Get Your Infrastructure Ready for Real-Time Analytics
9 March 2022, Built In

Pilosa: A Scalable High Performance Bitmap Database Index
17 June 2019, hackernoon.com

32 Data and Analytics Startups That Will Go Big, According to VCs
28 September 2021, Business Insider

The 10 Coolest Big Data Tools Of 2021
7 December 2021, CRN

provided by Google News

Share this page