DBMS > GridDB vs. InfluxDB vs. Oracle Coherence vs. PostgreSQL vs. Sphinx
System Properties Comparison GridDB vs. InfluxDB vs. Oracle Coherence vs. PostgreSQL vs. Sphinx
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Name | GridDB Xexclude from comparison | InfluxDB Xexclude from comparison | Oracle Coherence Xexclude from comparison | PostgreSQL Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Scalable in-memory time series database optimized for IoT and Big Data | DBMS for storing time series, events and metrics | Oracles in-memory data grid solution | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series DBMS | Time Series DBMS | Key-value store | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store Relational DBMS | Spatial DBMS with GEO package | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | griddb.net | www.influxdata.com/products/influxdb-overview | www.oracle.com/java/coherence | www.postgresql.org | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.griddb.net | docs.influxdata.com/influxdb | docs.oracle.com/en/middleware/standalone/coherence | www.postgresql.org/docs | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Toshiba Corporation | Oracle | PostgreSQL Global Development Group www.postgresql.org/developer | Sphinx Technologies Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2013 | 2007 | 1989 1989: Postgres, 1996: PostgreSQL | 2001 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.1, August 2022 | 2.7.5, January 2024 | 14.1, August 2023 | 16.2, February 2024 | 3.5.1, February 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | 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 | Open Source BSD | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | Go | Java | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux OS X through Homebrew | All OS with a Java VM | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | schema-free | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes numerical, string, blob, geometry, boolean, timestamp | Numeric data and Strings | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | no | yes | yes full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL92, SQL-like TQL (Toshiba Query Language) | SQL-like query language | no | yes standard with numerous extensions | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | HTTP API JSON over UDP | JCache JPA RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | 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 | .Net C++ Java | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | yes Live Events | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding in enterprise version only | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | selectable replication factor in enterprise version only | yes, with selectable consistency level | Source-replica replication other methods possible by using 3rd party extensions | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate consistency within container, eventual consistency across containers | Eventual Consistency Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID at container level | no | configurable | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optionally | yes | 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 | yes Depending on used storage engine | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per database | simple rights management via user accounts | authentification to access the cache via certificates or http basic authentication | fine grained access rights according to SQL-standard | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GridDB | InfluxDB | Oracle Coherence | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Sync Data from InfluxDB v2 to v3 With the Quix Template Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana Comparing Dates in Java: A Tutorial Python ARIMA Tutorial Time Series, InfluxDB, and Vector Databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GridDB | InfluxDB | Oracle Coherence | PostgreSQL | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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? | 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 | The DB-Engines ranking includes now search engines Monitoring PostgreSQL with Redgate Monitor 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 Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services 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 AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB provided by Google News Microservices with Major New Coherence and Helidon Releases Nike achieves scalability and performance with Oracle Coherence & Exadata New solutions for Oracle WebLogic on Azure Virtual Machines Oracle launches Oracle Banking Cloud Services - ThePaypers provided by Google News Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... PostgreSQL or MySQL: What Should I Choose for My Full-Stack Project? PeerDB raises $3.6M to accelerate PostgreSQL data movement Did One Guy Just Stop a Huge Cyberattack? provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ The Pirate Bay was recently down for over a week due to a DDoS attack How to Build 600+ Links in One Month Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial provided by Google News |
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