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DBMS > Ehcache vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. Milvus

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. Milvus

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value storeKey-value store
Wide column store
Relational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Websitewww.ehcache.orgcloud.google.com/­bigtablecloud.google.com/­spannermilvus.io
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docsmilvus.io/­docs/­overview.md
DeveloperTerracotta Inc, owned by Software AGGoogleGoogle
Initial release2009201520172019
Current release3.10.0, March 20222.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
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 languageJavaC++, Go
Server operating systemsAll OS with a Java VMhostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesVector, 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 indexesnonoyesno
SQL infoSupport of SQLnonoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
RESTful HTTP API
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononono
Triggersyes infoCache Event Listenersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rights
More information provided by the system vendor
EhcacheGoogle Cloud BigtableGoogle Cloud SpannerMilvus
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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EhcacheGoogle Cloud BigtableGoogle Cloud SpannerMilvus
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