DBMS > Badger vs. Elasticsearch vs. FatDB vs. SAP HANA

System Properties Comparison Badger vs. Elasticsearch vs. FatDB vs. SAP HANA

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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.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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.

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

Primary database model

Key-value store

Search engine

Document store
Key-value store

Relational 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	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/dgraph-io/badger

www.elastic.co/elasticsearch

www.sap.com/products/hana.html

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

help.sap.com/hana

Developer

DGraph Labs

Elastic

FatCloud

SAP

Initial release

2017

2010

2012

2010

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Elastic License

commercial

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Windows

Appliance or cloud-service

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

APIs and other access methods

Java API
RESTful HTTP/JSON API

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

JDBC
ODBC

Supported programming languages

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

Server-side scripts

Stored procedures

yes

via applications

SQLScript, R

Triggers

yes

by using the 'percolation' feature

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Can implement custom security layer via applications

yes

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