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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNatively in-memory DBMS with options for persistency, high-availability and clusteringA fast-speed and highly-scalable Graph DBMSA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Graph DBMSVector DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websiteimpala.apache.orgwww.mcobject.comgithub.com/­hugegraph
hugegraph.apache.org
milvus.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmhugegraph.apache.org/­docsmilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMcObjectBaidu
Initial release2013200120182019
Current release4.1.0, June 20228.2, 20210.92.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen 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++C and C++JavaC++, Go
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
macOS
Unix
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesVector, 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 infosupport of XML interfaces availablenono
Secondary indexesyesyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLnono
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
Lua
Python
Scala
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
Triggersnoyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning / shardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes 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 ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers, roles and permissionsRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaeXtremeDBHugeGraphMilvus
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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Apache ImpalaeXtremeDBHugeGraphMilvus
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