DBMS > atoti vs. Firebase Realtime Database vs. SAP HANA vs. Sequoiadb

System Properties Comparison atoti vs. Firebase Realtime Database vs. SAP HANA vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

NewSQL database with distributed OLTP and SQL

Primary database model

Object oriented DBMS

Document store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

atoti.io

firebase.google.com/products/realtime-database

www.sap.com/products/hana.html

www.sequoiadb.com

Technical documentation

docs.atoti.io

firebase.google.com/docs/database

help.sap.com/hana

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

ActiveViam

Google

acquired by Google 2014

SAP

Sequoiadb Ltd.

Initial release

2012

2010

2013

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

hosted

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

Java
JavaScript
Objective-C

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Python

limited functionality with using 'rules'

SQLScript, R

JavaScript

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

yes, based on authentication and database rules

yes

simple password-based access control

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