DBMS > Elasticsearch vs. HyperSQL vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison Elasticsearch vs. HyperSQL vs. Microsoft Azure Table Storage vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A Wide Column Store for rapid development using massive semi-structured datasets

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.elastic.co/elasticsearch

hsqldb.org

azure.microsoft.com/en-us/services/storage/tables

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Elastic

Microsoft

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2010

2001

2012

1992

2000

Current release

8.6, January 2023

2.7.2, June 2023

17, July 2015

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

based on BSD license

commercial

Open Source

Public Domain

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

Java

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

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

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

All languages supporting JDBC/ODBC
Java

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Java, SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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