DBMS > Alibaba Cloud Table Store vs. Google Cloud Firestore vs. KeyDB vs. Microsoft SQL Server vs. SpaceTime

System Properties Comparison Alibaba Cloud Table Store vs. Google Cloud Firestore vs. KeyDB vs. Microsoft SQL Server vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsofts flagship relational DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

www.alibabacloud.com/product/table-store

firebase.google.com/products/firestore

github.com/Snapchat/KeyDB
keydb.dev

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

www.mireo.com/spacetime

Technical documentation

www.alibabacloud.com/help/en/tablestore

firebase.google.com/docs/firestore

docs.keydb.dev

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

Developer

Alibaba

Google

EQ Alpha Technology Ltd.

Microsoft

Mireo

Initial release

2016

2017

2019

1989

2020

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

BSD-3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

hosted

Linux

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

APIs and other access methods

HTTP API

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

Proprietary protocol

RESP - REdis Serialization Protoco

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

RESTful HTTP API

Supported programming languages

Java
Python

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

C#
C++
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Lua

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

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

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

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

yes

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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 based on subaccounts and tokens

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

yes

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