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DBMS > BigObject vs. HBase vs. Kinetica vs. RavenDB

System Properties Comparison BigObject vs. HBase vs. Kinetica vs. RavenDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesWide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedWide column storeRelational DBMSDocument store
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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitebigobject.iohbase.apache.orgwww.kinetica.comravendb.net
Technical documentationdocs.bigobject.iohbase.apache.org/­book.htmldocs.kinetica.comravendb.net/­docs
DeveloperBigObject, Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetKineticaHibernating Rhinos
Initial release2015200820122010
Current release2.3.4, January 20217.1, August 20215.4, July 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache version 2commercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C#
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
Unix
Windows infousing Cygwin
LinuxLinux
macOS
Raspberry Pi
Windows
Data schemeyesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesno
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsSQL-like query language (RQL)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
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
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresLuayes infoCoprocessors in Javauser defined functionsyes
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationDefault 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 tablesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)noACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table levelAuthorization levels configured per client per database

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More resources
BigObjectHBaseKineticaRavenDB
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