DBMS > Google BigQuery vs. GridDB vs. InfluxDB vs. Oracle vs. PostgreSQL
System Properties Comparison Google BigQuery vs. GridDB vs. InfluxDB vs. Oracle vs. PostgreSQL
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| Name | Google BigQuery Xexclude from comparison | GridDB Xexclude from comparison | InfluxDB Xexclude from comparison | Oracle Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Large scale data warehouse service with append-only tables | Scalable in-memory time series database optimized for IoT and Big Data | DBMS for storing time series, events and metrics | Widely used RDBMS | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Time Series DBMS | Time Series DBMS | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Key-value store Relational DBMS | Spatial DBMS with GEO package | Document store Graph DBMS with Oracle Spatial and GraphRDF store with Oracle Spatial and GraphSpatial DBMS with Oracle Spatial and GraphVector DBMS since Oracle 23 | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | cloud.google.com/bigquery | griddb.net | www.influxdata.com/products/influxdb-overview | www.oracle.com/database | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | cloud.google.com/bigquery/docs | docs.griddb.net | docs.influxdata.com/influxdb | docs.oracle.com/en/database | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Toshiba Corporation | Oracle | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2010 | 2013 | 2013 | 1980 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 5.1, August 2022 | 2.7.6, April 2024 | 23c, September 2023 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available | Open Source MIT-License; commercial enterprise version available | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C++ | Go | C and C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux | Linux OS X through Homebrew | AIX HP-UX Linux OS X Solaris Windows z/OS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | schema-free | yes Schemaless in JSON and XML columns | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes numerical, string, blob, geometry, boolean, timestamp | Numeric data and Strings | yes | 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. | no | no | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | SQL92, SQL-like TQL (Toshiba Query Language) | SQL-like query language | yes with proprietary extensions | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | RESTful HTTP/JSON API | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | HTTP API JSON over UDP | JDBC ODBC ODP.NET Oracle Call Interface (OCI) | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net Java JavaScript Objective-C PHP Python Ruby | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | C C# C++ Clojure Cobol Delphi Eiffel Erlang Fortran Groovy Haskell Java JavaScript Lisp Objective C OCaml Perl PHP Python R Ruby Scala Tcl Visual Basic | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | user defined functions in JavaScript | no | no | PL/SQL also stored procedures in Java possible | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | none | Sharding | Sharding in enterprise version only | Sharding, horizontal partitioning | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | selectable replication factor in enterprise version only | Multi-source replication Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no can be realized in PL/SQL | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency within container, eventual consistency across containers | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Since BigQuery is designed for querying data | ACID at container level | no | ACID isolation level can be parameterized | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes Depending on used storage engine | yes Version 12c introduced the new option 'Oracle Database In-Memory' | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access privileges (owner, writer, reader) on dataset, table or view level Google Cloud Identity & Access Management (IAM) | Access rights for users can be defined per database | simple rights management via user accounts | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Google BigQuery | GridDB | InfluxDB | Oracle | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | GitHub trending repository » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | Open source core with closed source clustering available either on-premise or on... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB Deadman Alerts with Grafana and InfluxDB Cloud 3.0 Chasing the Skies: Monitoring Flights with InfluxDB Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Google BigQuery | GridDB | InfluxDB | Oracle | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Cloud-based DBMS's popularity grows at high rates | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Oracle Cloud World Winning the 2020 Google Cloud Technology Partner of the Year – Infrastructure Modernization Award Google Cloud partners Coinbase to accept crypto payments Hightouch Raises $38M in Funding provided by Google News General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ... General Availability of GridDB 5.3 Enterprise Edition ~ Major Enhancement in IoT and Time Series Data Analysis ... Toshiba launches cloudy managed IoT database service running its own GridDB GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ... General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ... provided by Google News Amazon Timestream for InfluxDB is now generally available Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB? provided by Google News Panasonic Information Systems Selects Oracle Cloud Infrastructure to Drive Modernization of Internal Systems Across ... Oracle And Google Partner To Deliver Multicloud Offering To Enterprises Oracle to colocate database services and network interconnect in Google data centers Oracle Q4 Stunners: RPO Soars 44% to $98 Billion, Google Cloud Is New BFF Oracle and Google Cloud Announce a Groundbreaking Multicloud Partnership provided by Google News PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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