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DBMS > Apache Impala vs. HyperSQL vs. Hyprcubd vs. Milvus

System Properties Comparison Apache Impala vs. HyperSQL vs. Hyprcubd vs. Milvus

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonMilvus  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBServerless Time Series DBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSRelational DBMSTime Series 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
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteimpala.apache.orghsqldb.orghyprcubd.com (offline)milvus.io
Technical documentationimpala.apache.org/­impala-docs.htmlhsqldb.org/­web/­hsqlDocsFrame.htmlmilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHyprcubd, Inc.
Initial release201320012019
Current release4.1.0, June 20222.7.2, June 20232.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infobased on BSD licensecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
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++JavaGoC++, Go
Server operating systemsLinuxAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modeshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringVector, 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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
HTTP API infoJDBC via HTTP
JDBC
ODBC
gRPC (https)RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC
Java
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava, SQLnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
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 ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
Durability infoSupport for making data persistentyesyesyesyes
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 Kerberosfine grained access rights according to SQL-standardtoken accessRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaHyperSQL infoalso known as HSQLDBHyprcubdMilvus
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...
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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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More resources
Apache ImpalaHyperSQL infoalso known as HSQLDBHyprcubdMilvus
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

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14 November 2022, TheServerSide.com

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How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News



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