DBMS > etcd vs. Firebase Realtime Database vs. SAP Adaptive Server

System Properties Comparison etcd vs. Firebase Realtime Database vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	37.12
Rank	#25	Overall
	#17	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

firebase.google.com/products/realtime-database

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

firebase.google.com/docs/database

help.sap.com/docs/SAP_ASE

Developer

Google

acquired by Google 2014

SAP, Sybase

Initial release

2012

1987

Current release

3.4, August 2019

16.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

C and C++

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

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

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java
JavaScript
Objective-C

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Java and Transact-SQL

Triggers

yes, watching key changes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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