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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHugeGraph  Xexclude from comparisonMilvus  Xexclude from comparisonOceanBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA fast-speed and highly-scalable Graph DBMSA DBMS designed for efficient storage of vector data and vector similarity searchesA distributed, high available RDBMS compatible with Oracle and MySQL
Primary database modelRelational DBMSGraph DBMSVector DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score1.57
Rank#149  Overall
#69  Relational DBMS
Websiteimpala.apache.orggithub.com/­hugegraph
hugegraph.apache.org
milvus.ioen.oceanbase.com
Technical documentationimpala.apache.org/­impala-docs.htmlhugegraph.apache.org/­docsmilvus.io/­docs/­overview.mden.oceanbase.com/­docs/­oceanbase-database
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaiduOceanBase infopreviously Alibaba and Ant Group
Initial release2013201820192010
Current release4.1.0, June 20220.92.3.4, January 20244.3.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoCommercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++JavaC++, GoC++
Server operating systemsLinuxLinux
macOS
Unix
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, 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.nononoyes
Secondary indexesyesyes infoalso supports composite index and range indexnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
Supported programming languagesAll languages supporting JDBC/ODBCGroovy
Java
Python
C++
Go
Java
JavaScript (Node.js)
Python
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardinghorizontal partitioning (by hash, key, range, range columns, list, and list columns)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducevia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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 KerberosUsers, roles and permissionsRole based access control and fine grained access rightsAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Apache ImpalaHugeGraphMilvusOceanBase
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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