DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Datastax Enterprise vs. Elasticsearch vs. InfinityDB vs. Milvus

System Properties Comparison Datastax Enterprise vs. Elasticsearch vs. InfinityDB vs. Milvus

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDatastax Enterprise  Xexclude from comparisonElasticsearch  Xexclude from comparisonInfinityDB  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA Java embedded Key-Value Store which extends the Java Map interfaceA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelWide column storeSearch engine
Vector DBMS
Key-value storeVector DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.00
Rank#66  Overall
#4  Wide column stores
Score123.81
Rank#9  Overall
#1  Search engines
#1  Vector DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Score2.92
Rank#87  Overall
#7  Vector DBMS
Websitewww.datastax.com/­products/­datastax-enterprisewww.elastic.co/­elasticsearchboilerbay.commilvus.io
Technical documentationdocs.datastax.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlboilerbay.com/­infinitydb/­manualmilvus.io/­docs/­overview.md
DeveloperDataStaxElasticBoiler Bay Inc.
Initial release2011201020022019
Current release6.8, April 20208.6, January 20234.02.4.4, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2.0
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.
Implementation languageJavaJavaJavaC++, Go
Server operating systemsLinux
OS X
All OS with a Java VMAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysVector, 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.nononono
Secondary indexesyesyes infoAll search fields are automatically indexedno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query languagenono
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Java API
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
JavaC++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyesnono
Triggersyesyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter aware, advanced replication for edge computingyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesES-Hadoop Connectornono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Eventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency infoREAD-COMMITTED or SERIALIZEDBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnoACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.yesMemcached and Redis integrationnoyes
User concepts infoAccess controlAccess rights for users can be defined per objectnoRole based access control and fine grained access rights

More information provided by the system vendor

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
Datastax EnterpriseElasticsearchInfinityDBMilvus
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

IBM to acquire DataStax, helping clients bring the power of unstructured data to enterprise AI applications
25 February 2025, IBM

Big Blue To Acquire Datastax in Enterprise AI Play
28 February 2025, Redmond Channel Partner

IBM to Acquire DataStax to Power Generative AI, Tapping into 93% of Enterprise Data
26 February 2025, eWEEK

IBM To Buy DataStax, Expand Watsonx AI Portfolio’s Data Management Capabilities
25 February 2025, CRN Magazine

IBM strengthens AI portfolio with acquisition of DataStax
26 February 2025, techzine.eu

provided by Google News

OpenSearch 3.0 hits: First major release under Linux Foundation as it battles ElasticSearch for mindshare
7 May 2025, devclass

OpenSearch in 2025: Much more than an Elasticsearch fork
28 April 2025, InfoWorld

Amazon OpenSearch Service announces Standard and Extended Support dates for Elasticsearch and OpenSearch versions
7 November 2024, Amazon Web Services (AWS)

Elasticsearch Now Available as a Native Grounding Engine on Google Cloud’s Vertex AI Platform
9 April 2025, Business Wire

Elasticsearch Was Great, But Vector Databases Are the Future
18 November 2024, The New Stack

provided by Google News

What Is Milvus? A Distributed Vector Database
3 March 2025, Oracle

Milvus 2.5 Creates the Best of Both Worlds With Hybrid Vector-Keyword Search
17 December 2024, GlobeNewswire

AI-Powered Search Engine With Milvus Vector Database on Vultr
7 November 2024, SitePoint

Dance between dense and sparse embeddings: Enabling Hybrid Search in LangChain-Milvus
19 November 2024, Towards Data Science

Why Manual Sharding is a Bad Idea for Vector Database And How to Fix It | by Milvus | Apr, 2025
25 April 2025, DataDrivenInvestor

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

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

Neo4j logo

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

Milvus logo

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

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Present your product here