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DBMS > FeatureBase vs. Vertica vs. Weaviate

System Properties Comparison FeatureBase vs. Vertica vs. Weaviate

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.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.An AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMS infoColumn orientedVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#296  Overall
#134  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Score1.48
Rank#149  Overall
#8  Vector DBMS
Websitewww.featurebase.comwww.vertica.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.featurebase.comvertica.com/­documentationweaviate.io/­developers/­weaviate
DeveloperMolecula and Pilosa Open Source ContributorsOpenText infopreviously Micro Focus and Hewlett PackardWeaviate B.V.
Initial release201720052019
Current release2022, May 202212.0.3, January 20231.19, May 2023
License infoCommercial or Open Sourcecommercialcommercial infoLimited community edition freeOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++Go
Server operating systemsLinux
macOS
Linux
Data schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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 indexesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.yes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL queriesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.GraphQL is used as query language
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesJava
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
FeatureBaseVertica infoOpenText™ Vertica™Weaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
FeatureBaseVertica infoOpenText™ Vertica™Weaviate
DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021,  Etienne Dilocker, SeMI Technologies (sponsor) 

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