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DBMS > Apache Impala vs. LeanXcale vs. LevelDB vs. Netezza

System Properties Comparison Apache Impala vs. LeanXcale vs. LevelDB vs. Netezza

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonLeanXcale  Xexclude from comparisonLevelDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websiteimpala.apache.orgwww.leanxcale.comgithub.com/­google/­leveldbwww.ibm.com/­products/­netezza
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaLeanXcaleGoogleIBM
Initial release2013201520112000
Current release4.1.0, June 20221.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxIllumos
Linux
OS X
Windows
Linux infoincluded in appliance
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infothrough Apache Derbynoyes
APIs and other access methodsJDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
Java
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoUsers with fine-grained authorization concept

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More resources
Apache ImpalaLeanXcaleLevelDBNetezza infoAlso called PureData System for Analytics by IBM
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