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DBMS > Google Cloud Bigtable vs. Netezza vs. Solr vs. StarRocks

System Properties Comparison Google Cloud Bigtable vs. Netezza vs. Solr vs. StarRocks

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSolr  Xexclude from comparisonStarRocks  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.Data warehouse and analytics appliance part of IBM PureSystemsA widely used distributed, scalable search engine based on Apache LuceneAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelKey-value store
Wide column store
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­netezzasolr.apache.orgwww.starrocks.io
Technical documentationcloud.google.com/­bigtable/­docssolr.apache.org/­resources.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperGoogleIBMApache Software FoundationThe Linux Foundation infosince Feb 2023
Initial release2015200020062020
Current release9.6.1, May 20242.5.3, March 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java
Server operating systemshostedLinux infoincluded in applianceAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typingyes
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.noyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyesSolr Parallel SQL Interfaceyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
JDBC
MySQL protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Server-side scripts infoStored proceduresnoyesJava pluginsuser defined functions
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDoptimistic lockingno
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptyesRole based access control and fine grained access rights

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More resources
Google Cloud BigtableNetezza infoAlso called PureData System for Analytics by IBMSolrStarRocks
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