DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. Google BigQuery vs. InfluxDB vs. Oracle Berkeley DB vs. RavenDB

System Properties Comparison Amazon Aurora vs. Google BigQuery vs. InfluxDB vs. Oracle Berkeley DB vs. RavenDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonInfluxDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonLarge scale data warehouse service with append-only tablesDBMS for storing time series, events and metricsWidely used in-process key-value storeOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document store
Secondary database modelsDocument storeSpatial DBMS infowith GEO packageGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.05
Rank#49  Overall
#31  Relational DBMS
Score62.67
Rank#19  Overall
#13  Relational DBMS
Score26.89
Rank#28  Overall
#1  Time Series DBMS
Score2.80
Rank#112  Overall
#20  Key-value stores
#3  Native XML DBMS
Score3.47
Rank#95  Overall
#16  Document stores
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­bigquerywww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlravendb.net
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigquery/­docsdocs.influxdata.com/­influxdbdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlravendb.net/­docs
DeveloperAmazonGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleHibernating Rhinos
Initial release20152010201319942010
Current release2.7.5, January 202418.1.40, May 20205.4, July 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infocommercial license availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, Java, C++ (depending on the Berkeley DB edition)C#
Server operating systemshostedhostedLinux
OS X infothrough Homebrew
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringsnono
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.yesnonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyesyesSQL-like query languageyes infoSQL interfaced based on SQLite is availableSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIHTTP API
JSON over UDP
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions infoin JavaScriptnonoyes
Triggersyesnonoyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding infoin enterprise version onlynoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infoin enterprise version onlySource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoSince BigQuery is designed for querying datanoACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoDepending on used storage engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)simple rights management via user accountsnoAuthorization levels configured per client per database
More information provided by the system vendor
Amazon AuroraGoogle BigQueryInfluxDBOracle Berkeley DBRavenDB
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

Time Series, InfluxDB, and Vector Databases
26 March 2024

Machine Learning and Infrastructure Monitoring: Tools and Justification
20 March 2024

Making Most Recent Value Queries Hundreds of Times Faster
18 March 2024

Telegraf 1.30 Release Notes
15 March 2024

Tale of the Tape: Data Historians vs Time Series Databases
13 March 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
Amazon AuroraGoogle BigQueryInfluxDBOracle Berkeley DBRavenDB
DB-Engines blog posts

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

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

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

Amazon Aurora MySQL version 2 (with MySQL 5.7 compatibility) to version 3 (with MySQL 8.0 compatibility) upgrade ...
18 March 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

Knowledge Bases for Amazon Bedrock now supports Amazon Aurora PostgreSQL and Cohere embedding models ...
12 February 2024, AWS Blog

Amazon Aurora MySQL zero-ETL integration with Amazon Redshift is now generally available | Amazon Web Services
7 November 2023, AWS Blog

provided by Google News

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

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

Google’s Logica language addresses SQL’s flaws
15 April 2021, InfoWorld

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

Google Cloud Platform breaks through with big enterprises, signs up Disney and others
23 March 2016, ZDNet

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

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

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

How Apache Arrow accelerates InfluxDB
21 November 2023, InfoWorld

provided by Google News

Fedora Looking To Transition The RPM Database From Berkeley DB To SQLite
16 March 2020, Phoronix

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

The importance of bitcoin nodes and how to start one
9 May 2014, The Merkle Hash

provided by Google News

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

Oren Eini on RavenDB, Including Consistency Guarantees and C# as the Implementation Language
23 May 2022, InfoQ.com

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

RavenDB Adds Graph Queries
15 May 2019, Datanami

provided by Google News



Share this page

Featured Products

Neo4j logo

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

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

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here