DBMS > Elasticsearch vs. NuoDB vs. SAP HANA vs. Sphinx vs. WakandaDB

System Properties Comparison Elasticsearch vs. NuoDB vs. SAP HANA vs. Sphinx 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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

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	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.elastic.co/elasticsearch

www.3ds.com/nuodb-distributed-sql-database

www.sap.com/products/hana.html

sphinxsearch.com

wakanda.github.io

Technical documentation

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

doc.nuodb.com

help.sap.com/hana

sphinxsearch.com/docs

wakanda.github.io/doc

Developer

Elastic

Dassault Systèmes

originally NuoDB, Inc.

SAP

Sphinx Technologies Inc.

Wakanda SAS

Initial release

2010

2013

2010

2001

2012

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Elastic License

commercial

limited edition free

commercial

Open Source

GPL version 2, commercial licence available

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++

C++, JavaScript

Server operating systems

All OS with a Java VM

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Appliance or cloud-service

FreeBSD
Linux
NetBSD
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.

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
ODBC

Proprietary protocol

RESTful HTTP API

Supported programming languages

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

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript

Server-side scripts

Stored procedures

yes

Java, SQL

SQLScript, R

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

yes

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

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Temporary table

yes

User concepts

Access control

Standard SQL roles/ privileges, Administrative Users

yes

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