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DBMS > BigObject vs. Google Cloud Bigtable vs. HBase vs. Kinetica

System Properties Comparison BigObject vs. Google Cloud Bigtable vs. HBase vs. Kinetica

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Wide column store
Wide column storeRelational DBMS
Secondary database modelsSpatial 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitebigobject.iocloud.google.com/­bigtablehbase.apache.orgwww.kinetica.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docshbase.apache.org/­book.htmldocs.kinetica.com
DeveloperBigObject, Inc.GoogleApache Software Foundation infoApache top-level project, originally developed by PowersetKinetica
Initial release2015201520082012
Current release2.3.4, January 20217.1, August 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
Unix
Windows infousing Cygwin
Linux
Data schemeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes
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 indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuanoyes infoCoprocessors in Javauser defined functions
Triggersnonoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsSingle row ACID (across millions of columns)no
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.yesnoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table level

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More resources
BigObjectGoogle Cloud BigtableHBaseKinetica
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