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DBMS > Apache Impala vs. Blazegraph vs. HugeGraph vs. Milvus

System Properties Comparison Apache Impala vs. Blazegraph vs. HugeGraph vs. Milvus

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBlazegraph  Xexclude from comparisonHugeGraph  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.
DescriptionAnalytic DBMS for HadoopHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A fast-speed and highly-scalable Graph DBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSGraph DBMS
RDF store
Graph DBMSVector DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.77
Rank#222  Overall
#20  Graph DBMS
#8  RDF stores
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Websiteimpala.apache.orgblazegraph.comgithub.com/­hugegraph
hugegraph.apache.org
milvus.io
Technical documentationimpala.apache.org/­impala-docs.htmlwiki.blazegraph.comhugegraph.apache.org/­docsmilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBlazegraphBaidu
Initial release2013200620182019
Current release4.1.0, June 20222.1.5, March 20190.92.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoextended commercial license availableOpen Source infoApache Version 2.0Open Source infoApache Version 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 Milvus
Implementation languageC++JavaJavaC++, Go
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS
Unix
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesVector, 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.nonono
Secondary indexesyesyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLSQL-like DML and DDL statementsSPARQL is used as query languagenono
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Groovy
Java
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesasynchronous Gremlin script jobsno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyes infoRelationships in Graphsyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity and Authentication via Web Application Container (Tomcat, Jetty)Users, roles and permissionsRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaBlazegraphHugeGraphMilvus
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
Apache ImpalaBlazegraphHugeGraphMilvus
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