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DBMS > Apache Phoenix vs. InfinityDB vs. QuestDB vs. RDF4J

System Properties Comparison Apache Phoenix vs. InfinityDB vs. QuestDB vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonQuestDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 dataRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value storeTime Series DBMSRDF store
Secondary database modelsRelational 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
Score0.69
Rank#230  Overall
#9  RDF stores
Websitephoenix.apache.orgboilerbay.comquestdb.iordf4j.org
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualquestdb.io/­docsrdf4j.org/­documentation
DeveloperApache Software FoundationBoiler Bay Inc.QuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2014200220142004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava (Zero-GC), C++, RustJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
macOS
Windows
Linux
OS X
Unix
Windows
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 infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nonono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynoyes
SQL infoSupport of SQLyesnoSQL with time-series extensionsno
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
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityno
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 writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infothrough memory mapped files
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono
More information provided by the system vendor
Apache PhoenixInfinityDBQuestDBRDF4J infoformerly known as Sesame
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 PhoenixInfinityDBQuestDBRDF4J infoformerly known as Sesame
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