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DBMS > Apache Impala vs. Apache IoTDB vs. Graph Engine vs. HEAVY.AI

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Graph Engine vs. HEAVY.AI

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelRelational DBMSTime Series DBMSGraph DBMS
Key-value store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.56
Rank#241  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.41
Rank#153  Overall
#71  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.graphengine.iogithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.heavy.ai
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationMicrosoftHEAVY.AI, Inc.
Initial release2013201820102016
Current release4.1.0, June 20221.1.0, April 20235.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java.NET and CC++ and CUDA
Server operating systemsLinuxAll OS with a Java VM (>= 1.8).NETLinux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyes
APIs and other access methodsJDBC
ODBC
JDBC
Native API
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaApache IoTDBGraph Engine infoformer name: TrinityHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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