DBMS > Apache Impala vs. CrateDB vs. EJDB vs. H2GIS

System Properties Comparison Apache Impala vs. CrateDB vs. EJDB vs. H2GIS

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed Database based on Lucene

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Spatial extension of H2

Primary database model

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Spatial DBMS

Secondary database models

Document store

Relational DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Website

impala.apache.org

cratedb.com

github.com/Softmotions/ejdb

www.h2gis.org

Technical documentation

impala.apache.org/impala-docs.html

cratedb.com/docs

github.com/Softmotions/ejdb/blob/master/README.md

www.h2gis.org/docs/home

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Crate

Softmotions

CNRS

Initial release

2013

2012

2013

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2

Open Source

LGPL 3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

server-less

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

in-process shared library

Supported programming languages

All languages supporting JDBC/ODBC

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions (Javascript)

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Configurable replication on table/partition-level

none

yes

based on H2

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

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

yes

based on H2

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More resources

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

AWS Marketplace: CrateDB Cloud Comments
12 June 2024, AWS Blog

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8 April 2024, Datanami

CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT
25 March 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, businesswire.com

provided by Google News

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