DBMS > Elasticsearch vs. Heroic vs. IBM Db2 warehouse vs. OpenTenBase

System Properties Comparison Elasticsearch vs. Heroic vs. IBM Db2 warehouse vs. OpenTenBase

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Cloud-based data warehousing service

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Search engine

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	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

www.elastic.co/elasticsearch

github.com/spotify/heroic

www.ibm.com/products/db2/warehouse

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

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

spotify.github.io/heroic

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Elastic

Spotify

IBM

OpenAtom Foundation, previously Tencent

Initial release

2010

2014

Current release

8.6, January 2023

2.5, January 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

commercial

Open Source

BSD-3

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

hosted

Linux

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.

Import/export of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

yes

PL/SQL, SQL PL

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency
Immediate Consistency

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

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

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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

AWS hands OpenSearch to Linux Foundation – is this why Elasticsearch was made open source again?
16 September 2024, DevClass

The Elasticsearch cloud now subject to open-source licence
3 September 2024, TechHQ

Elastic Announces Open Source License for Elasticsearch and Kibana Source Code
29 August 2024, businesswire.com

Elasticsearch Open Inference API Extends Support for Hugging Face Models with Semantic Text
12 September 2024, Yahoo Finance

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

provided by Google News

A major upgrade to Db2® Warehouse on IBM Cloud®
26 June 2024, IBM

Announcing the deprecation of prior generation Db2 Warehouse plans on AWS
16 October 2023, IBM

The 10 Best Cloud Data Warehouse Solutions to Consider in 2024
22 October 2023, Solutions Review

Data Mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

provided by Google News

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