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DBMS > Databricks vs. Google Cloud Bigtable vs. Sequoiadb vs. Tkrzw vs. Yaacomo

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. Sequoiadb vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSequoiadb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.NewSQL database with distributed OLTP and SQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL 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
Document store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.databricks.comcloud.google.com/­bigtablewww.sequoiadb.comdbmx.net/­tkrzwyaacomo.com
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksGoogleSequoiadb Ltd.Mikio HirabayashiQ2WEB GmbH
Initial release20132015201320202009
Current release0.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedhostedLinuxLinux
macOS
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes infooid, date, timestamp, binary, regexnoyes
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.yesnononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languagenoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
PHP
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJavaScriptno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsDocument is locked during a transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infousing specific database classesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGoogle Cloud BigtableSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud BigtableSequoiadbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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