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 > Pinecone vs. Trafodion vs. Vertica

System Properties Comparison Pinecone vs. Trafodion vs. Vertica

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonTrafodion  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA managed, cloud-native vector databaseTransactional SQL-on-Hadoop DBMSCloud 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 modelVector DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.pinecone.iotrafodion.apache.orgwww.vertica.com
Technical documentationdocs.pinecone.io/­docs/­overviewtrafodion.apache.org/­documentation.htmlvertica.com/­documentation
DeveloperPinecone Systems, IncApache Software Foundation, originally developed by HPOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201920142005
Current release2.3.0, February 201912.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++
Server operating systemshostedLinuxLinux
Data schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateString, Number, Booleanyesyes
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 indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPythonAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HBaseMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBaseno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
PineconeTrafodionVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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

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

More resources
PineconeTrafodionVertica infoOpenText™ Vertica™
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Pinecone launches serverless edition of its vector database on AWS
22 May 2024, SiliconANGLE News

Channel Brief: Dell Explains AI Factory, Informatica AI Research, Pinecone Goes Serverless and More
22 May 2024, Channel E2E

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone Launches Serverless Vector Database for Scalable AI Applications
21 May 2024, Datanami

How a Decades-Old Technology and a Paper From Meta Created an AI Industry Standard
21 May 2024, The Wall Street Journal

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

How Embedded Analytics Help ISVs Overcome Challenges
14 September 2023, Spiceworks News and Insights

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

OpenText integrates Micro Focus tech through Cloud Editions 23.3
26 July 2023, Techzine Europe

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.

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

RaimaDB logo

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

SingleStore logo

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

Present your product here