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DBMS > BigObject vs. Kinetica vs. LevelDB vs. RavenDB vs. Spark SQL

System Properties Comparison BigObject vs. Kinetica vs. LevelDB vs. RavenDB vs. Spark SQL

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebigobject.iowww.kinetica.comgithub.com/­google/­leveldbravendb.netspark.apache.org/­sql
Technical documentationdocs.bigobject.iodocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBigObject, Inc.KineticaGoogleHibernating RhinosApache Software Foundation
Initial release20152012201120102014
Current release7.1, August 20211.23, February 20215.4, July 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoBSDOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++C#Scala
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxIllumos
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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 indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoSQL-like query language (RQL)SQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuauser defined functionsnoyesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnoneMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles on table levelnoAuthorization levels configured per client per databaseno

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More resources
BigObjectKineticaLevelDBRavenDBSpark SQL
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