DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Graphite vs. Ignite vs. Milvus vs. Tkrzw

System Properties Comparison Graphite vs. Ignite vs. Milvus vs. Tkrzw

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGraphite  Xexclude from comparisonIgnite  Xexclude from comparisonMilvus  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A DBMS designed for efficient storage of vector data and vector similarity searchesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Vector DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­graphite-project/­graphite-webignite.apache.orgmilvus.iodbmx.net/­tkrzw
Technical documentationgraphite.readthedocs.ioapacheignite.readme.io/­docsmilvus.io/­docs/­overview.md
DeveloperChris DavisApache Software FoundationMikio Hirabayashi
Initial release2006201520192020
Current releaseApache Ignite 2.62.3.4, January 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open 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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languagePythonC++, Java, .NetC++, GoC++
Server operating systemsLinux
Unix
Linux
OS X
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateNumeric data onlyyesVector, Numeric and Stringno
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.noyesnono
Secondary indexesnoyesno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnono
APIs and other access methodsHTTP API
Sockets
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesJavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)nono
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infolockingyesyesyes
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.yesyesyes infousing specific database classes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsRole based access control and fine grained access rightsno
More information provided by the system vendor
GraphiteIgniteMilvusTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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
GraphiteIgniteMilvusTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The value of time series data and TSDBs
10 June 2021, InfoWorld

Getting Started with Infrastructure Monitoring
11 September 2023, The New Stack

provided by Google News

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

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

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

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

Zilliz Cloud boosts vector database performance
31 January 2024, InfoWorld

provided by Google News



Share this page

Featured Products

Milvus logo

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

Neo4j logo

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

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

RaimaDB logo

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

Present your product here