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DBMS > Apache Phoenix vs. InfinityDB vs. QuestDB vs. Solr

System Properties Comparison Apache Phoenix vs. InfinityDB vs. QuestDB vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Java embedded Key-Value Store which extends the Java Map interfaceA high performance open source SQL database for time series dataA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeTime Series DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgboilerbay.comquestdb.iosolr.apache.org
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualquestdb.io/­docssolr.apache.org/­resources.html
DeveloperApache Software FoundationBoiler Bay Inc.QuestDB Technology IncApache Software Foundation
Initial release2014200220142006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.09.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava (Zero-GC), C++, RustJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoschema-free via InfluxDB Line Protocolyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes 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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSQL with time-series extensionsSolr Parallel SQL Interface
APIs and other access methodsJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnonoJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replication with eventual consistencyyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate 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 dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID for single-table writesoptimistic 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.yesnoyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoyes
More information provided by the system vendor
Apache PhoenixInfinityDBQuestDBSolr
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache PhoenixInfinityDBQuestDBSolr
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