DBMS > GridDB vs. MongoDB vs. Oracle Rdb vs. Stardog vs. Vertica
System Properties Comparison GridDB vs. MongoDB vs. Oracle Rdb vs. Stardog vs. Vertica
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Name | GridDB Xexclude from comparison | MongoDB Xexclude from comparison | Oracle Rdb Xexclude from comparison | Stardog Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Scalable in-memory time series database optimized for IoT and Big Data | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Time Series DBMS | Document store | Relational DBMS | Graph DBMS RDF store | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store Relational DBMS | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | griddb.net | www.mongodb.com | www.oracle.com/database/technologies/related/rdb.html | www.stardog.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.griddb.net | www.mongodb.com/docs/manual | www.oracle.com/database/technologies/related/rdb-doc.html | docs.stardog.com | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Toshiba Corporation | MongoDB, Inc | Oracle, originally developed by Digital Equipment Corporation (DEC) | Stardog-Union | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2009 | 1984 | 2010 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.1, August 2022 | 6.0.7, June 2023 | 7.4.1.1, 2021 | 7.3.0, May 2020 | 12.0.3, January 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 MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | commercial | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no MongoDB available as DBaaS (MongoDB Atlas) | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | C++ | Java | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux OS X Solaris Windows | HP Open VMS | Linux macOS Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | Flexible Schema (defined schema, partial schema, schema free) | schema-free and OWL/RDFS-schema support | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes numerical, string, blob, geometry, boolean, timestamp | yes string, integer, double, decimal, boolean, date, object_id, geospatial | yes | 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 Import/export of XML data possible | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes supports real-time indexing in full-text and geospatial | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL92, SQL-like TQL (Toshiba Query Language) | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | GraphQL HTTP REST Prisma proprietary protocol using JSON | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | .Net Clojure Groovy Java JavaScript Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | JavaScript | user defined functions and aggregates, HTTP Server extensions in Java | yes, PostgreSQL PL/pgSQL, with minor differences | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes in MongoDB Atlas only | yes via event handlers | yes, called Custom Alerts | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | none | horizontal partitioning, hierarchical partitioning | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | Multi-source replication in HA-Cluster | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate consistency within container, eventual consistency across containers | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | Immediate Consistency in HA-Cluster | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no typically not used, however similar functionality with DBRef possible | yes | yes relationships in graphs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID at container level | Multi-document ACID Transactions with snapshot isolation | yes, on a single node | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes optional, enabled by default | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes In-memory storage engine introduced with MongoDB version 3.2 | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per database | Access rights for users and roles | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GridDB | MongoDB | Oracle Rdb | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | Built around the flexible document data model and unified API, MongoDB is a developer... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GitHub trending repository » more | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Studio 3T: The world's favorite IDE for working with MongoDB » more CData: Connect to Big Data & NoSQL through standard Drivers. » more Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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GridDB | MongoDB | Oracle Rdb | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ... 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 ... Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ... provided by Google News | MongoDB Atlas Vector Search integration now GA with Amazon Bedrock Build RAG applications with MongoDB Atlas, now available in Knowledge Bases for Amazon Bedrock | Amazon Web ... MongoDB aims to jumpstart AI app development with MAAP The Google/MongoDB tie-in: Gemini Code Assist analyzed MongoDB Launches 'One-Stop-Shop' Program For Building Advanced GenAI Applications provided by Google News | Oracle Adds New AI-Enabling Features To MySQL HeatWave Oracle Business Model - How Oracle Makes Money? Should we all consolidate databases for the storage benefits? Reg vultures deploy DevOps, zoos, haircuts 2013 Data Science Salary Survey – O'Reilly provided by Google News | OCI Object Storage Completes Technical Validation of Vertica in Eon Mode Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities MapR Hadoop Upgrade Runs HP Vertica Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations provided by Google News |
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