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DBMS > Databricks vs. HarperDB vs. Hypertable

System Properties Comparison Databricks vs. HarperDB vs. Hypertable

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHarperDB  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 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.An open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelDocument store
Relational DBMS
Document storeWide column store
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
Websitewww.databricks.comwww.harperdb.io
Technical documentationdocs.databricks.comdocs.harperdb.io/­docs
DeveloperDatabricksHarperDBHypertable Inc.
Initial release201320172009
Current release3.1, August 20210.9.8.11, March 2016
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC++
Server operating systemshostedLinux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Data schemeFlexible Schema (defined schema, partial schema, schema free)dynamic schemaschema-free
Typing infopredefined data types such as float or dateyes infoJSON data typesno
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.yesno
Secondary indexesyesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLwith Databricks SQLSQL-like data manipulation statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
C++ API
Thrift
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++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesCustom Functions infosince release 3.1no
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infothe nodes on which a table resides can be definedselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesno
More information provided by the system vendor
DatabricksHarperDBHypertable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHarperDBHypertable
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