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DBMS > AlaSQL vs. GridDB vs. HEAVY.AI vs. Milvus

System Properties Comparison AlaSQL vs. GridDB vs. HEAVY.AI vs. Milvus

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Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionJavaScript DBMS libraryScalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMSVector DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitealasql.orggriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
milvus.io
Technical documentationgithub.com/­AlaSQL/­alasqldocs.griddb.netdocs.heavy.aimilvus.io/­docs/­overview.md
DeveloperAndrey Gershun & Mathias R. WulffToshiba CorporationHEAVY.AI, Inc.
Initial release2014201320162019
Current release5.1, August 20225.10, January 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoMIT-LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0
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 languageJavaScriptC++C++ and CUDAC++, Go
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesVector, 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 indexesnoyesnono
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsJavaScript APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
RESTful HTTP API
Supported programming languagesJavaScriptC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlnoAccess rights for users can be defined per databasefine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
AlaSQLGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Milvus
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsGitHub trending repository
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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AlaSQLGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Milvus
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