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DBMS > Databricks vs. HarperDB vs. IBM Db2 Event Store vs. Tkrzw vs. Yaacomo

System Properties Comparison Databricks vs. HarperDB vs. IBM Db2 Event Store vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHarperDB  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.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
Score0.60
Rank#244  Overall
#38  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.comwww.harperdb.iowww.ibm.com/­products/­db2-event-storedbmx.net/­tkrzwyaacomo.com
Technical documentationdocs.databricks.comdocs.harperdb.io/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperDatabricksHarperDBIBMMikio HirabayashiQ2WEB GmbH
Initial release20132017201720202009
Current release3.1, August 20212.00.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercial infofree developer edition availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC and C++C++
Server operating systemshostedLinux
OS X
Linux infoLinux, macOS, Windows for the developer additionLinux
macOS
Android
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)dynamic schemayesschema-freeyes
Typing infopredefined data types such as float or dateyes infoJSON data typesyesnoyes
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 SQLSQL-like data manipulation statementsyes infothrough the embedded Spark runtimenoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
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 aggregatesCustom Functions infosince release 3.1yesno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infothe nodes on which a table resides can be definedActive-active shard replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
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 dataACIDAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyes, using LMDBYes - 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.noyesyesyes infousing specific database classesyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHarperDBIBM 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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DatabricksHarperDBIBM Db2 Event StoreTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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