DBMS > Elasticsearch vs. Firebase Realtime Database vs. SAP HANA vs. Sphinx vs. StarRocks

System Properties Comparison Elasticsearch vs. Firebase Realtime Database vs. SAP HANA vs. Sphinx vs. StarRocks

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

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	13.64
Rank	#39	Overall
	#6	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

www.elastic.co/elasticsearch

firebase.google.com/products/realtime-database

www.sap.com/products/hana.html

sphinxsearch.com

www.starrocks.io

Technical documentation

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

firebase.google.com/docs/database

help.sap.com/hana

sphinxsearch.com/docs

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Elastic

Google

acquired by Google 2014

SAP

Sphinx Technologies Inc.

The Linux Foundation

since Feb 2023

Initial release

2010

2012

2010

2001

2020

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

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++, Java

Server operating systems

All OS with a Java VM

hosted

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

Proprietary protocol

JDBC
MySQL protocol

Supported programming languages

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

Java
JavaScript
Objective-C

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Java

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

SQLScript, R

user defined functions

Triggers

yes

by using the 'percolation' feature

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

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

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

yes, based on authentication and database rules

yes

Role based access control and fine grained access rights

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.