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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHeroic  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpark 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 modelKey-value store
Wide column store
Time Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­spotify/­heroicspark.apache.org/­sqlyaacomo.com
Technical documentationcloud.google.com/­bigtable/­docsspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleSpotifyApache Software FoundationQ2WEB GmbH
Initial release2015201420142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono
Secondary indexesnoyes infovia Elasticsearchnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
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

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More resources
Google Cloud BigtableHeroicSpark SQLYaacomo
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