DBMS > Axibase vs. Cachelot.io vs. Datomic vs. Google Cloud Firestore vs. Microsoft SQL Server

System Properties Comparison Axibase vs. Cachelot.io vs. Datomic vs. Google Cloud Firestore vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

In-memory caching system

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

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	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

cachelot.io

www.datomic.com

firebase.google.com/products/firestore

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

Technical documentation

docs.datomic.com

firebase.google.com/docs/firestore

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

Developer

Axibase Corporation

Cognitect

Google

Microsoft

Initial release

2013

2015

2012

2017

1989

Current release

15585

1.0.7075, December 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Simplified BSD License

commercial

limited edition free

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java, Clojure

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Memcached protocol

RESTful HTTP API

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

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

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Clojure
Java

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

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, Firebase Rules & Cloud Functions

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

Triggers

yes

By using transaction functions

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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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