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

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

Editorial information provided by DB-Engines

Name

Description

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

In-memory caching system

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

Analytics Platform for Big Data

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	7.36
Rank	#53	Overall
	#9	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

axibase.com/docs/atsd/finance

cachelot.io

firebase.google.com/products/firestore

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

www.splunk.com

Technical documentation

firebase.google.com/docs/firestore

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

docs.splunk.com/Documentation/Splunk

Developer

Axibase Corporation

Google

Microsoft

Splunk Inc.

Initial release

2013

2015

2017

1989

2003

Current release

15585

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

restricted free version is available

commercial

Limited free edition and free developer edition 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++

Server operating systems

Linux

FreeBSD
Linux
OS X

hosted

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

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

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Memcached protocol

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

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

HTTP REST

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

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

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

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

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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.

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

Access rights for users and roles

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