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DBMS > Hive vs. Solr vs. TimescaleDB vs. WakandaDB

System Properties Comparison Hive vs. Solr vs. TimescaleDB vs. WakandaDB

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSSearch engineTime Series DBMSObject oriented DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitehive.apache.orgsolr.apache.orgwww.timescale.comwakanda.github.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homesolr.apache.org/­resources.htmldocs.timescale.comwakanda.github.io/­doc
DeveloperApache Software Foundation infoinitially developed by FacebookApache Software FoundationTimescaleWakanda SAS
Initial release2012200620172012
Current release3.1.3, April 20229.6.1, May 20242.15.0, May 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++, JavaScript
Server operating systemsAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.yesyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
Thrift
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesC++
Java
PHP
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersnoyes infoUser configurable commands triggered on index changesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducespark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDACID
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.yesnono
User concepts infoAccess controlAccess rights for users, groups and rolesyesfine grained access rights according to SQL-standardyes

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More resources
HiveSolrTimescaleDBWakandaDB
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