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

System Properties Comparison Google Cloud Bigtable vs. HEAVY.AI vs. Lovefield 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 comparisonLovefield  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 hardwareEmbeddable relational database for web apps written in pure JavaScriptA 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 DBMSSpatial 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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitecloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
google.github.io/­lovefieldsolr.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.html
DeveloperGoogleHEAVY.AI, Inc.GoogleApache Software Foundation
Initial release2015201620142006
Current release5.10, January 20222.1.12, February 20179.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0Open 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 CUDAJavaScriptJava
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAll 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.nononoyes
Secondary indexesnonoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesSQL-like query language infovia JavaScript builder patternSolr Parallel SQL Interface
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava plugins
TriggersnonoUsing read-only observersyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationnoneyes
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 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 persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDByes
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-standardnoyes

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