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DBMS > BigObject vs. Coveo vs. LevelDB vs. Spark SQL

System Properties Comparison BigObject vs. Coveo vs. LevelDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCoveo  Xexclude from comparisonLevelDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedSearch engineKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score2.28
Rank#114  Overall
#11  Search engines
Score2.35
Rank#111  Overall
#19  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebigobject.iowww.coveo.comgithub.com/­google/­leveldbspark.apache.org/­sql
Technical documentationdocs.bigobject.iodocs.coveo.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBigObject, Inc.CoveoGoogleApache Software Foundation
Initial release2015201220112014
Current release1.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedIllumos
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuanonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyesnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlnogranular access controls, API key management, content filtersnono

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BigObjectCoveoLevelDBSpark SQL
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