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DBMS > Apache Impala vs. HEAVY.AI vs. IRONdb vs. Microsoft Access

System Properties Comparison Apache Impala vs. HEAVY.AI vs. IRONdb vs. Microsoft Access

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.circonus.com/solutions/time-series-database/www.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationimpala.apache.org/­impala-docs.htmldocs.heavy.aidocs.circonus.com/irondb/category/getting-starteddeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHEAVY.AI, Inc.Circonus LLC.Microsoft
Initial release2013201620171992
Current release4.1.0, June 20225.10, January 2022V0.10.20, January 20181902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; enterprise edition availablecommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAC and C++C++
Server operating systemsLinuxLinuxLinuxWindows infoNot a real database server, but making use of DLLs
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes
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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (Circonus Analytics Query Language: CAQL)yes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Thrift
Vega
HTTP APIADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, in Luayes infosince Access 2010 using the ACE-engine
Triggersnononoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
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 Kerberosfine grained access rights according to SQL-standardnono infoa simple user-level security was built in till version Access 2003

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More resources
Apache ImpalaHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IRONdbMicrosoft Access
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