DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Milvus vs. Newts vs. RavenDB

System Properties Comparison Apache Impala vs. Milvus vs. Newts vs. RavenDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMilvus  Xexclude from comparisonNewts  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA DBMS designed for efficient storage of vector data and vector similarity searchesTime Series DBMS based on CassandraOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSVector DBMSTime Series DBMSDocument store
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score3.01
Rank#101  Overall
#17  Document stores
Websiteimpala.apache.orgmilvus.ioopennms.github.io/­newtsravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmlmilvus.io/­docs/­overview.mdgithub.com/­OpenNMS/­newts/­wikiravendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOpenNMS GroupHibernating Rhinos
Initial release2013201920142010
Current release4.1.0, June 20222.3.4, January 20245.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL version 3, commercial license available
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++, GoJavaC#
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyesno
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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIHTTP REST
Java API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC++
Go
Java
JavaScript (Node.js)
Python
Java.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID, Cluster-wide transaction available
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole based access control and fine grained access rightsnoAuthorization levels configured per client per database
More information provided by the system vendor
Apache ImpalaMilvusNewtsRavenDB
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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaMilvusNewtsRavenDB
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

What Is Milvus Vector Database?
6 October 2023, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Cloud boosts vector database performance
31 January 2024, InfoWorld

provided by Google News

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

RavenDB Adds Graph Queries
15 May 2019, Datanami

Review: NoSQL database RavenDB
20 March 2019, TechGenix

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here