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DBMS > Databricks vs. FeatureBase vs. Google BigQuery

System Properties Comparison Databricks vs. FeatureBase vs. Google BigQuery

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFeatureBase  Xexclude from comparisonGoogle BigQuery  Xexclude from comparison
DescriptionThe 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.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Large scale data warehouse service with append-only tables
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.26
Rank#304  Overall
#138  Relational DBMS
Score61.90
Rank#19  Overall
#13  Relational DBMS
Websitewww.databricks.comwww.featurebase.comcloud.google.com/­bigquery
Technical documentationdocs.databricks.comdocs.featurebase.comcloud.google.com/­bigquery/­docs
DeveloperDatabricksMolecula and Pilosa Open Source ContributorsGoogle
Initial release201320172010
Current release2022, May 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGo
Server operating systemshostedLinux
macOS
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyesnono
SQL infoSupport of SQLwith Databricks SQLSQL queriesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JDBC
Kafka Connector
ODBC
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Java
Python
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functions infoin JavaScript
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesno infoSince BigQuery is designed for querying data
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)
More information provided by the system vendor
DatabricksFeatureBaseGoogle BigQuery
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFeatureBaseGoogle BigQuery
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