DBMS > InfluxDB vs. Microsoft SQL Server vs. PlanetScale vs. SpaceTime vs. Sphinx

System Properties Comparison InfluxDB vs. Microsoft SQL Server vs. PlanetScale vs. SpaceTime vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

Microsofts flagship relational DBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

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

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

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.influxdata.com/products/influxdb-overview

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

planetscale.com

www.mireo.com/spacetime

sphinxsearch.com

Technical documentation

docs.influxdata.com/influxdb

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

planetscale.com/docs

sphinxsearch.com/docs

Developer

Microsoft

PlanetScale

Mireo

Sphinx Technologies Inc.

Initial release

2013

1989

2020

2001

Current release

2.7.6, April 2024

SQL Server 2022, November 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

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.

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Implementation language

C++

Server operating systems

Linux
OS X

through Homebrew

Linux
Windows

Docker
Linux
macOS

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

A subset of ANSI SQL is implemented

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP API
JSON over UDP

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

ADO.NET
JDBC
MySQL protocol
ODBC

RESTful HTTP API

Proprietary protocol

Supported programming languages

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

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

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

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

Sharding

Fixed-grid hypercubes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Real-time block device replication (DRBD)

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 across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

Depending on used storage engine

yes

User concepts

Access control

simple rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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News

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.