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DBMS > Apache Impala vs. LeanXcale vs. Netezza vs. RavenDB vs. Solr

System Properties Comparison Apache Impala vs. LeanXcale vs. Netezza vs. RavenDB vs. Solr

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonLeanXcale  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSDocument storeSearch engine
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgwww.leanxcale.comwww.ibm.com/­products/­netezzaravendb.netsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlravendb.net/­docssolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaLeanXcaleIBMHibernating RhinosApache Software Foundation
Initial release20132015200020102006
Current release4.1.0, June 20225.4, July 20229.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Java
Server operating systemsLinuxLinux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnoyes 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.noyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough Apache DerbyyesSQL-like query language (RQL)Solr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
Java
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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-reduceyesyesJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, Cluster-wide transaction availableoptimistic locking
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization conceptAuthorization levels configured per client per databaseyes

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More resources
Apache ImpalaLeanXcaleNetezza infoAlso called PureData System for Analytics by IBMRavenDBSolr
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