DBMS > Google Cloud Firestore vs. Microsoft SQL Server vs. NSDb vs. OpenTSDB vs. Teradata Aster

System Properties Comparison Google Cloud Firestore vs. Microsoft SQL Server vs. NSDb vs. OpenTSDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Scalable Time Series DBMS based on HBase

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Website

firebase.google.com/products/firestore

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

nsdb.io

opentsdb.net

Technical documentation

firebase.google.com/docs/firestore

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

nsdb.io/Architecture

opentsdb.net/docs/build/html/index.html

Developer

Google

Microsoft

currently maintained by Yahoo and other contributors

Teradata

Initial release

2017

1989

2017

2011

2005

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

LGPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Java, Scala

Java

Server operating systems

hosted

Linux
Windows

Linux
macOS

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

numeric data for metrics, strings for tags

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.

yes

in Aster File Store

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

gRPC
HTTP REST
WebSocket

HTTP API
Telnet API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

Java
Scala

Erlang
Go
Java
Python
R
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

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

R packages

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

selectable replication factor

based on HBase

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Immediate Consistency or Eventual Consistency depending on configuration

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

Using Apache Lucene

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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