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DBMS > Apache Impala vs. Milvus vs. RocksDB vs. Rockset

System Properties Comparison Apache Impala vs. Milvus vs. RocksDB vs. Rockset

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMilvus  Xexclude from comparisonRocksDB  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesEmbeddable persistent key-value store optimized for fast storage (flash and RAM)A scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMSVector DBMSKey-value storeDocument store
Secondary database modelsDocument storeRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score3.41
Rank#86  Overall
#11  Key-value stores
Score0.82
Rank#212  Overall
#36  Document stores
Websiteimpala.apache.orgmilvus.iorocksdb.orgrockset.com
Technical documentationimpala.apache.org/­impala-docs.htmlmilvus.io/­docs/­overview.mdgithub.com/­facebook/­rocksdb/­wikidocs.rockset.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFacebook, Inc.Rockset
Initial release2013201920132019
Current release4.1.0, June 20222.3.4, January 20249.2.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
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++, GoC++C++
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linuxhosted
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringnodynamic typing
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 infoingestion from XML files supported
Secondary indexesyesnonoall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIC++ API
Java API
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBCC++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
Perl
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesno
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 KerberosRole based access control and fine grained access rightsnoAccess rights for users and organizations can be defined via Rockset console
More information provided by the system vendor
Apache ImpalaMilvusRocksDBRockset
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
Apache ImpalaMilvusRocksDBRockset
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