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DBMS > Google Cloud Bigtable vs. HEAVY.AI vs. Kingbase vs. Solr

System Properties Comparison Google Cloud Bigtable vs. HEAVY.AI vs. Kingbase vs. Solr

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKingbase  Xexclude from comparisonSolr  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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Spatial 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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitecloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kingbase.com.cnsolr.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.heavy.aisolr.apache.org/­resources.html
DeveloperGoogleHEAVY.AI, Inc.BeiJing KINGBASE Information technologies inc.Apache Software Foundation
Initial release2015201619992006
Current release5.10, January 2022V8.0, August 20219.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC and JavaJava
Server operating systemshostedLinuxLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesnonoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesStandard with numerous extensionsSolr Parallel SQL Interface
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonouser defined functionsJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinhorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDoptimistic locking
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes

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