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DBMS > BoltDB vs. Databricks vs. GridGain vs. Weaviate

System Properties Comparison BoltDB vs. Databricks vs. GridGain vs. Weaviate

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Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionAn embedded key-value store for Go.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.GridGain is an in-memory computing platform, built on Apache IgniteAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelKey-value storeDocument store
Relational DBMS
Key-value store
Relational DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score1.52
Rank#153  Overall
#6  Vector DBMS
Websitegithub.com/­boltdb/­boltwww.databricks.comwww.gridgain.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmlweaviate.io/­developers/­weaviate
DeveloperDatabricksGridGain Systems, Inc.Weaviate B.V.
Initial release2013201320072019
Current releaseGridGain 8.5.11.19, May 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, C++, .NetGo
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes, maps to GraphQL interface
Typing infopredefined data types such as float or datenoyesyes 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.noyesyesno
Secondary indexesnoyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnowith Databricks SQLANSI-99 for query and DML statements, subset of DDLGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesGoPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
BoltDBDatabricksGridGainWeaviate
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
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Key customersAll companies that have data. ​
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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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BoltDBDatabricksGridGainWeaviate
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