DBMS > Amazon Neptune vs. Firebase Realtime Database vs. Microsoft SQL Server vs. Rockset vs. Sphinx

System Properties Comparison Amazon Neptune vs. Firebase Realtime Database vs. Microsoft SQL Server vs. Rockset vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/neptune

firebase.google.com/products/realtime-database

www.microsoft.com/en-us/sql-server

rockset.com

sphinxsearch.com

Technical documentation

aws.amazon.com/neptune/developer-resources

firebase.google.com/docs/database

learn.microsoft.com/en-US/sql/sql-server

docs.rockset.com

sphinxsearch.com/docs

Developer

Amazon

Google

acquired by Google 2014

Microsoft

Rockset

Sphinx Technologies Inc.

Initial release

2017

2012

1989

2019

2001

Current release

SQL Server 2022, November 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

hosted

Linux
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

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.

yes

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

SQL-like query language (SphinxQL)

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Android
iOS
JavaScript API
RESTful HTTP API

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

HTTP REST

Proprietary protocol

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes, but depending on the SQL-Server Edition

yes

none

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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.