DBMS > Databend vs. Elasticsearch vs. EventStoreDB vs. Heroic

System Properties Comparison Databend vs. Elasticsearch vs. EventStoreDB vs. Heroic

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

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	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.elastic.co/elasticsearch

www.eventstore.com

github.com/spotify/heroic

Technical documentation

docs.databend.com

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

developers.eventstore.com

spotify.github.io/heroic

Developer

Databend Labs

Elastic

Event Store Limited

Spotify

Initial release

2021

2010

2012

2014

Current release

1.0.59, April 2023

8.6, January 2023

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

Java

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

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

schema-free

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

via Elasticsearch

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

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

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Transaction concepts

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

yes

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

User concepts

Access control

Users with fine-grained authorization concept, user roles

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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

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3 July 2017, Matthias Gelbmann

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

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