DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Apache Impala vs. Elasticsearch vs. Lovefield vs. RDF4J

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Apache Impala vs. Elasticsearch vs. Lovefield vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Analytic DBMS for Hadoop

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Embeddable relational database for web apps written in pure JavaScript

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Document store

Document store
Spatial DBMS
Vector DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.alibabacloud.com/product/analyticdb-for-mysql

impala.apache.org

www.elastic.co/elasticsearch

google.github.io/lovefield

rdf4j.org

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

impala.apache.org/impala-docs.html

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/google/lovefield/blob/master/docs/spec_index.md

rdf4j.org/documentation

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Elastic

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2013

2010

2014

2004

Current release

4.1.0, June 2022

8.6, January 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

JavaScript

Java

Server operating systems

hosted

Linux

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

RDF Schemas

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
Java
PHP
Python

All languages supporting JDBC/ODBC

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

by using the 'percolation' feature

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

Memcached and Redis integration

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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