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DBMS > Apache Spark (SQL) vs. Google Cloud Bigtable

System Properties Comparison Apache Spark (SQL) vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.73
Rank#35  Overall
#20  Relational DBMS
Score2.91
Rank#93  Overall
#15  Key-value stores
#8  Wide column stores
Websitespark.apache.org/­sqlcloud.google.com/­bigtable
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlcloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationGoogle
Initial release20142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
hosted
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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.nono
Secondary indexesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesJava
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache Spark (SQL)Google Cloud Bigtable
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