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DBMS > BigObject vs. ReductStore vs. Spark SQL

System Properties Comparison BigObject vs. ReductStore vs. Spark SQL

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonReductStore  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebigobject.iogithub.com/­reductstore
www.reduct.store
spark.apache.org/­sql
Technical documentationdocs.bigobject.iowww.reduct.store/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBigObject, Inc.ReductStore LLCApache Software Foundation
Initial release201520232014
Current release1.9, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoBusiness Source License 1.1Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, RustScala
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesC++
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuano
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnone
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnono

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More resources
BigObjectReductStoreSpark SQL
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