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DBMS > Apache Phoenix vs. HarperDB vs. Hive vs. QuestDB

System Properties Comparison Apache Phoenix vs. HarperDB vs. Hive vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.data warehouse software for querying and managing large distributed datasets, built on HadoopA high performance open source SQL database for time series data
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMS
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
Score0.55
Rank#248  Overall
#38  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitephoenix.apache.orgwww.harperdb.iohive.apache.orgquestdb.io
Technical documentationphoenix.apache.orgdocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Homequestdb.io/­docs
DeveloperApache Software FoundationHarperDBApache Software Foundation infoinitially developed by FacebookQuestDB Technology Inc
Initial release2014201720122014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1, August 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJavaJava (Zero-GC), C++, Rust
Server operating systemsLinux
Unix
Windows
Linux
OS X
All OS with a Java VMLinux
macOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesdynamic schemayesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like data manipulation statementsSQL-like DML and DDL statementsSQL with time-series extensions
APIs and other access methodsJDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
PHP
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresuser defined functionsCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedselectable replication factorSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infothrough memory mapped files
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and rolesAccess rights for users, groups and roles
More information provided by the system vendor
Apache PhoenixHarperDBHiveQuestDB
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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