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DBMS > Apache IoTDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL vs. Vertica

System Properties Comparison Apache IoTDB vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processingCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelTime Series DBMSRelational DBMSVector DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­services/­synapse-analyticsmilvus.iospark.apache.org/­sqlwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentation
DeveloperApache Software FoundationMicrosoftApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20182016201920142005
Current release1.1.0, April 20232.3.4, January 20243.5.0 ( 2.13), September 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
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 languageJavaC++C++, GoScalaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyesyes
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 indexesyesyesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesTransact SQLnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding, horizontal partitioningShardingyes, utilizing Spark Corehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
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.yesyesnono
User concepts infoAccess controlyesyesRole based access control and fine grained access rightsnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQLVertica infoOpenText™ Vertica™
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» 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
Cost-based models and subscription-based models are both available. One license is...
» more

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Apache IoTDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQLVertica infoOpenText™ Vertica™
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