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DBMS > Google Cloud Bigtable vs. JaguarDB vs. MarkLogic vs. Milvus

System Properties Comparison Google Cloud Bigtable vs. JaguarDB vs. MarkLogic vs. Milvus

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonJaguarDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Performant, highly scalable DBMS for AI and IoT applicationsOperational and transactional Enterprise NoSQL databaseA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value store
Wide column store
Key-value store
Vector DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.00
Rank#385  Overall
#61  Key-value stores
#16  Vector DBMS
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitecloud.google.com/­bigtablewww.jaguardb.comwww.progress.com/­marklogicmilvus.io
Technical documentationcloud.google.com/­bigtable/­docswww.jaguardb.com/­support.htmlwww.progress.com/­marklogic/­documentationmilvus.io/­docs/­overview.md
DeveloperGoogleDataJaguar, Inc.MarkLogic Corp.
Initial release2015201520012019
Current release3.3 July 202311.0, December 20222.4.4, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0commercial inforestricted free version is availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++ infothe server part. Clients available in other languagesC++C++, Go
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesschema-free infoSchema can be enforced
Typing infopredefined data types such as float or datenoyesyesVector, 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.nonoyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes infoSQL92no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScriptno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsRole-based access control at the document and subdocument levelsRole based access control and fine grained access rights
More information provided by the system vendor
Google Cloud BigtableJaguarDBMarkLogicMilvus
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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More resources
Google Cloud BigtableJaguarDBMarkLogicMilvus
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Conferences, events and webinars

Progress MarkLogic World
Washington DC, 23-25 September 2024 (finished)

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