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DBMS > Google Cloud Bigtable vs. InterSystems Caché vs. Milvus vs. Oracle Coherence

System Properties Comparison Google Cloud Bigtable vs. InterSystems Caché vs. Milvus vs. Oracle Coherence

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMilvus  Xexclude from comparisonOracle Coherence  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application serverA DBMS designed for efficient storage of vector data and vector similarity searchesOracles in-memory data grid solution
Primary database modelKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Vector DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Websitecloud.google.com/­bigtablewww.intersystems.com/­products/­cachemilvus.iowww.oracle.com/­java/­coherence
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.commilvus.io/­docs/­overview.mddocs.oracle.com/­en/­middleware/­standalone/­coherence
DeveloperGoogleInterSystemsOracle
Initial release2015199720192007
Current release2018.1.4, May 20202.3.4, January 202414.1, August 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial
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++, GoJava
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java VM
Data schemeschema-freedepending on used data modelschema-free
Typing infopredefined data types such as float or datenoyesVector, 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.noyesnono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoyesnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJCache
JPA
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
Server-side scripts infoStored proceduresnoyesnono
Triggersnoyesnoyes infoLive Events
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infooptionally
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesRole based access control and fine grained access rightsauthentification to access the cache via certificates or http basic authentication
More information provided by the system vendor
Google Cloud BigtableInterSystems CachéMilvusOracle Coherence
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 BigtableInterSystems CachéMilvusOracle Coherence
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