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DBMS > FatDB vs. Milvus vs. Spark SQL vs. YugabyteDB

System Properties Comparison FatDB vs. Milvus vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelDocument store
Key-value store
Vector DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitemilvus.iospark.apache.org/­sqlwww.yugabyte.com
Technical documentationmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperFatCloudApache Software FoundationYugabyte Inc.
Initial release2012201920142017
Current release2.3.4, January 20243.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 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 MilvusYugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC#C++, GoScalaC and C++
Server operating systemsWindowsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
OS X
Data schemeschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesVector, 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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesC#C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnonoyes infosql, plpgsql, C
Triggersyes infovia applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole based access control and fine grained access rightsnoyes
More information provided by the system vendor
FatDBMilvusSpark SQLYugabyteDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Systems of record and engagement for cloud native applications that require resilience,...
» 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
2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more
Apache 2.0 license for the database
» more

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More resources
FatDBMilvusSpark SQLYugabyteDB
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