DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google BigQuery vs. InfluxDB vs. Netezza vs. SiriDB

System Properties Comparison Google BigQuery vs. InfluxDB vs. Netezza vs. SiriDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonInfluxDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSiriDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesDBMS for storing time series, events and metricsData warehouse and analytics appliance part of IBM PureSystemsOpen Source Time Series DBMS
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websitecloud.google.com/­bigquerywww.influxdata.com/­products/­influxdb-overviewwww.ibm.com/­products/­netezzasiridb.com
Technical documentationcloud.google.com/­bigquery/­docsdocs.influxdata.com/­influxdbdocs.siridb.com
DeveloperGoogleIBMCesbit
Initial release2010201320002017
Current release2.7.6, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC
Server operating systemshostedLinux
OS X infothrough Homebrew
Linux infoincluded in applianceLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyesyes infoNumeric data
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLyesSQL-like query languageyesno
APIs and other access methodsRESTful HTTP/JSON APIHTTP API
JSON over UDP
JDBC
ODBC
OLE DB
HTTP API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoin enterprise version onlyShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlySource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoDepending on used storage engineyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)simple rights management via user accountsUsers with fine-grained authorization conceptsimple rights management via user accounts
More information provided by the system vendor
Google BigQueryInfluxDBNetezza infoAlso called PureData System for Analytics by IBMSiriDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
News

Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API
23 May 2024

What is DevRel at InfluxData
21 May 2024

An Introductory Guide to Grafana Alerts
16 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google BigQueryInfluxDBNetezza infoAlso called PureData System for Analytics by IBMSiriDB
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2022, defending the title from last year
3 January 2023, Matthias Gelbmann, Paul Andlinger

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Winning the 2020 Google Cloud Technology Partner of the Year – Infrastructure Modernization Award
22 December 2021, CIO

Google Cloud partners Coinbase to accept crypto payments
11 October 2022, Ledger Insights

Hightouch Announces $38M in Funding and Launches New Customer 360 Toolkit
20 July 2023, Datanami

Google Cloud Starts Accepting Crypto Payments via Partnership with Coinbase
12 October 2022, CoinTrust

Hightouch Raises $38M in Funding
19 July 2023, FinSMEs

provided by Google News

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB
5 April 2024, VentureBeat

provided by Google News

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

Netezza Performance Server
12 August 2020, IBM

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here