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DBMS > Apache Impala vs. Databend vs. EsgynDB vs. Solr vs. Yaacomo

System Properties Comparison Apache Impala vs. Databend vs. EsgynDB vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabend  Xexclude from comparisonEsgynDB  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic DBMS for HadoopAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
www.esgyn.cnsolr.apache.orgyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databend.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabend LabsEsgynApache Software FoundationQ2WEB GmbH
Initial release20132021201520062009
Current release4.1.0, June 20221.0.59, April 20239.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++RustC++, JavaJava
Server operating systemsLinuxhosted
Linux
macOS
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingyes
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.nononoyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Rust
All languages supporting JDBC/ODBC/ADO.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored ProceduresJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication between multi datacentersyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept, user rolesfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaDatabendEsgynDBSolrYaacomo
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