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DBMS > Google Cloud Bigtable vs. InfinityDB vs. Solr vs. VictoriaMetrics

System Properties Comparison Google Cloud Bigtable vs. InfinityDB vs. Solr vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInfinityDB  Xexclude from comparisonSolr  Xexclude from comparisonVictoriaMetrics  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 Java embedded Key-Value Store which extends the Java Map interfaceA widely used distributed, scalable search engine based on Apache LuceneA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value store
Wide column store
Key-value storeSearch engineTime Series 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
Score0.08
Rank#365  Overall
#55  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitecloud.google.com/­bigtableboilerbay.comsolr.apache.orgvictoriametrics.com
Technical documentationcloud.google.com/­bigtable/­docsboilerbay.com/­infinitydb/­manualsolr.apache.org/­resources.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleBoiler Bay Inc.Apache Software FoundationVictoriaMetrics
Initial release2015200220062018
Current release4.09.6.1, May 2024v1.91, May 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGo
Server operating systemshostedAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nonoyesno
Secondary indexesnono infomanual creation possible, using inversions based on multi-value capabilityyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Java API
RESTful HTTP/JSON API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Java.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyesSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-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)Immediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsoptimistic 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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes

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More resources
Google Cloud BigtableInfinityDBSolrVictoriaMetrics
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