DBMS > Elasticsearch vs. FatDB vs. TempoIQ vs. VoltDB

System Properties Comparison Elasticsearch vs. FatDB vs. TempoIQ vs. VoltDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Search engine

Document store
Key-value store

Time Series DBMS

Relational DBMS

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	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.elastic.co/elasticsearch

tempoiq.com (offline)

www.voltdb.com

Technical documentation

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

docs.voltdb.com

Developer

Elastic

FatCloud

TempoIQ

VoltDB Inc.

Initial release

2010

2012

2010

Current release

8.6, January 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

All OS with a Java VM

Windows

Linux
OS X

for development

Data scheme

schema-free

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

schema-free

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

SQL

Support of SQL

SQL-like query language

Via inetgration in SQL Server

yes

only a subset of SQL 99

APIs and other access methods

Java API
RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C#
Java
JavaScript

Node.js
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

Java

Triggers

yes

by using the 'percolation' feature

yes

via applications

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

Memcached and Redis integration

User concepts

Access control

Can implement custom security layer via applications

simple authentication-based access control

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

Elasticsearch Changes Name to Elastic to Reflect Wide Adoption Beyond Search
29 April 2024, Yahoo Singapore News

Elastic Reports 8x Speed and 32x Efficiency Gains for Elasticsearch and Lucene Vector Database
26 April 2024, Business Wire

The end of vendor-backed open source?
29 April 2024, InfoWorld

Splunk vs Elasticsearch | A Comparison and How to Choose
12 January 2024, SentinelOne

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8 things to consider when applying for an accelerator from 2 C-level execs
29 May 2015, Built In Chicago

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16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

provided by Google News

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