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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGreenplum  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNatively in-memory DBMS with options for persistency, high-availability and clusteringAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMSVector DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Websiteimpala.apache.orgwww.mcobject.comgreenplum.orgmilvus.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmdocs.greenplum.orgmilvus.io/­docs/­overview.md
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMcObjectPivotal Software Inc.
Initial release2013200120052019
Current release4.1.0, June 20228.2, 20217.0.0, September 20232.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
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++C and C++C++, Go
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
LinuxLinux
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 availableyes infosince Version 4.2no
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLyesno
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
Lua
Python
Scala
C
Java
Perl
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesno
Triggersnoyes infoby defining eventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning / shardingShardingSharding
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
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyesno
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.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardRole based access control and fine grained access rights
More information provided by the system vendor
Apache ImpalaeXtremeDBGreenplumMilvus
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...
» more
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...
» more
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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More resources
Apache ImpalaeXtremeDBGreenplumMilvus
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