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DBMS > Apache Impala vs. Hypertable vs. Milvus vs. Vitess

System Properties Comparison Apache Impala vs. Hypertable vs. Milvus vs. Vitess

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonMilvus  Xexclude from comparisonVitess  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn open source BigTable implementation based on distributed file systems such as HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSWide column storeVector DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websiteimpala.apache.orgmilvus.iovitess.io
Technical documentationimpala.apache.org/­impala-docs.htmlmilvus.io/­docs/­overview.mdvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.The Linux Foundation, PlanetScale
Initial release2013200920192013
Current release4.1.0, June 20220.9.8.11, March 20162.4.4, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
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++C++C++, GoGo
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoVector, Numeric and Stringyes
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.nono
Secondary indexesyesrestricted infoonly exact value or prefix value scansnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes infoproprietary syntax
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache ImpalaHypertableMilvusVitess
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 ImpalaHypertableMilvusVitess
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