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DBMS > Google Cloud Bigtable vs. GridGain vs. HEAVY.AI vs. Kinetica

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. HEAVY.AI vs. Kinetica

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelKey-value store
Wide column store
Key-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitecloud.google.com/­bigtablewww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmldocs.heavy.aidocs.kinetica.com
DeveloperGoogleGridGain Systems, Inc.HEAVY.AI, Inc.Kinetica
Initial release2015200720162012
Current releaseGridGain 8.5.15.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++ and CUDAC, C++
Server operating systemshostedLinux
OS X
Solaris
Windows
LinuxLinux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyesnono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLyesSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)nouser defined functions
Triggersnoyes (cache interceptors and events)noyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Google Cloud BigtableGridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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