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DBMS > Blazegraph vs. Firebolt vs. Google Cloud Datastore vs. Milvus

System Properties Comparison Blazegraph vs. Firebolt vs. Google Cloud Datastore vs. Milvus

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonFirebolt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMilvus  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteblazegraph.comwww.firebolt.iocloud.google.com/­datastoremilvus.io
Technical documentationwiki.blazegraph.comdocs.firebolt.iocloud.google.com/­datastore/­docsmilvus.io/­docs/­overview.md
DeveloperBlazegraphFirebolt Analytics Inc.Google
Initial release2006202020082019
Current release2.1.5, March 20192.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoextended commercial license 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 systemsLinux
OS X
Windows
hostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyes, details hereVector, 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.nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageyesSQL-like query language (GQL)no
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.Net
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Go
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnousing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesdepending on storage layerMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)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
BlazegraphFireboltGoogle Cloud DatastoreMilvus
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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BlazegraphFireboltGoogle Cloud DatastoreMilvus
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