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DBMS > Databricks vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. Tkrzw vs. Yaacomo

System Properties Comparison Databricks vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIBM Db2 Event Store  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Distributed Event Store optimized for Internet of Things use casesA 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
Document storeEvent Store
Time Series 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
Score7.36
Rank#53  Overall
#9  Document stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.databricks.comfirebase.google.com/­products/­firestorewww.ibm.com/­products/­db2-event-storedbmx.net/­tkrzwyaacomo.com
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­firestorewww.ibm.com/­docs/­en/­db2-event-store
DeveloperDatabricksGoogleIBMMikio HirabayashiQ2WEB GmbH
Initial release20132017201720202009
Current release2.00.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++
Server operating systemshostedhostedLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyes infothrough the embedded Spark runtimenoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes, Firebase Rules & Cloud Functionsyesno
Triggersyes, with Cloud Functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationActive-active shard replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGoogle Cloud FirestoreIBM Db2 Event StoreTkrzw 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 FirestoreIBM Db2 Event StoreTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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