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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Milvus vs. SpatiaLite

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Milvus vs. SpatiaLite

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMilvus  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A DBMS designed for efficient storage of vector data and vector similarity searchesSpatial extension of SQLite
Primary database modelRelational DBMSKey-value store
Wide column store
Vector DBMSSpatial DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablemilvus.iowww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsmilvus.io/­docs/­overview.mdwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleAlessandro Furieri
Initial release2013201520192008
Current release4.1.0, June 20222.3.4, January 20245.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenoyesnono
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++
Server operating systemsLinuxhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoVector, 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.nononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rightsno
More information provided by the system vendor
Apache ImpalaGoogle Cloud BigtableMilvusSpatiaLite
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 ImpalaGoogle Cloud BigtableMilvusSpatiaLite
DB-Engines blog posts

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