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DBMS > Apache Impala vs. Datomic vs. Faircom EDGE vs. Solr

System Properties Comparison Apache Impala vs. Datomic vs. Faircom EDGE vs. Solr

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgwww.datomic.comwww.faircom.com/­products/­faircom-edgesolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectFairCom CorporationApache Software Foundation
Initial release2013201219792006
Current release4.1.0, June 20221.0.6735, June 2023V3, October 20209.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureANSI C, C++Java
Server operating systemsLinuxAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes 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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoANSI SQL queriesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.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-reduceyes infoTransaction Functionsyes info.Net, JavaScript, C/C++Java plugins
TriggersnoBy using transaction functionsyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yes

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More resources
Apache ImpalaDatomicFaircom EDGE infoformerly c-treeEDGESolr
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