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DBMS > Apache Impala vs. Hazelcast vs. Manticore Search vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. Hazelcast vs. Manticore Search vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA widely adopted in-memory data gridMulti-storage database for search, including full-text search.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value storeSearch engineWide column store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteimpala.apache.orghazelcast.commanticoresearch.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmlhazelcast.org/­imdg/­docsmanual.manticoresearch.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHazelcastManticore SoftwareMicrosoft
Initial release2013200820172012
Current release4.1.0, June 20225.3.6, November 20236.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
macOS
Windows
hosted
Data schemeyesschema-freeFixed schemaschema-free
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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 infothe object must implement a serialization strategyCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageno
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoEvent Listeners, Executor Servicesuser defined functionsno
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoReplicated MapSynchronous replication based on Galera libraryyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedyes infoisolated transactions for atomic changes and binary logging for safe writesoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlnoAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaHazelcastManticore SearchMicrosoft Azure Table Storage
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