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DBMS > Databricks vs. HarperDB vs. Oracle Berkeley DB vs. SingleStore

System Properties Comparison Databricks vs. HarperDB vs. Oracle Berkeley DB vs. SingleStore

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHarperDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
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.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Widely used in-process key-value storeMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelDocument store
Relational DBMS
Document storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitewww.databricks.comwww.harperdb.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.singlestore.com
Technical documentationdocs.databricks.comdocs.harperdb.io/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmldocs.singlestore.com
DeveloperDatabricksHarperDBOracle infooriginally developed by Sleepycat, which was acquired by OracleSingleStore Inc.
Initial release2013201719942013
Current release3.1, August 202118.1.40, May 20208.5, January 2024
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infocommercial license availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC, Java, C++ (depending on the Berkeley DB edition)C++, Go
Server operating systemshostedLinux
OS X
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux info64 bit version required
Data schemeFlexible Schema (defined schema, partial schema, schema free)dynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyes infoJSON data typesnoyes
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.yesnoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-like data manipulation statementsyes infoSQL interfaced based on SQLite is availableyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesCustom Functions infosince release 3.1noyes
Triggersnoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusternoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infothe nodes on which a table resides can be definedSource-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes, using LMDByesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users and rolesnoFine grained access control via users, groups and roles
More information provided by the system vendor
DatabricksHarperDBOracle Berkeley DBSingleStore infoformer name was MemSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
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