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DBMS > Apache Impala vs. Apache IoTDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Milvus

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Milvus

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  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 FlinkTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSRelational DBMSVector 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteimpala.apache.orgiotdb.apache.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlspotify.github.io/­heroicdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationSpotifyMicrosoft
Initial release20132018201420162019
Current release4.1.0, June 20221.1.0, April 20232.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++JavaJavaC++C++, Go
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesVector, Numeric and String
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.nonononono
Secondary indexesyesyesyes infovia Elasticsearchyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyesno
APIs and other access methodsJDBC
ODBC
JDBC
Native API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoTransact SQLno
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding, horizontal partitioningSharding
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 replicasyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
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.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesyesRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaApache IoTDBHeroicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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Apache ImpalaApache IoTDBHeroicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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