DBMS > Elasticsearch vs. Infobright vs. SAP HANA vs. SAP SQL Anywhere vs. WakandaDB

System Properties Comparison Elasticsearch vs. Infobright vs. SAP HANA vs. SAP SQL Anywhere vs. WakandaDB

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

In-memory, column based data store. Available as appliance or cloud service

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Search engine

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.elastic.co/elasticsearch

ignitetech.com/softwarelibrary/infobrightdb

www.sap.com/products/hana.html

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

wakanda.github.io

Technical documentation

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

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

wakanda.github.io/doc

Developer

Elastic

Ignite Technologies Inc.; formerly InfoBright Inc.

SAP

formerly Sybase

Wakanda SAS

Initial release

2010

2005

2010

1992

2012

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Elastic License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, JavaScript

Server operating systems

All OS with a Java VM

Linux
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

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

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

Secondary indexes

yes

All search fields are automatically indexed

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

JavaScript

Server-side scripts

Stored procedures

yes

SQLScript, R

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

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

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

Concurrency

Support for concurrent manipulation of data

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.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

fine grained access rights according to SQL-standard

yes

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