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DBMS > Databricks vs. Google Cloud Bigtable vs. Spark SQL vs. Yaacomo

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Spark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.databricks.comcloud.google.com/­bigtablespark.apache.org/­sqlyaacomo.com
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabricksGoogleApache Software FoundationQ2WEB GmbH
Initial release2013201520142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostedhostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.yesnonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
JDBC
ODBC
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGoogle Cloud BigtableSpark SQLYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud BigtableSpark SQLYaacomo
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