DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > EsgynDB vs. Memcached vs. Vitess vs. Warp 10

System Properties Comparison EsgynDB vs. Memcached vs. Vitess vs. Warp 10

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMemcached  Xexclude from comparisonVitess  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionIn-memory key-value store, originally intended for cachingScalable, distributed, cloud-native DBMS, extending MySQLTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.88
Rank#203  Overall
#95  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.esgyn.cnwww.memcached.orgvitess.iowww.warp10.io
Technical documentationgithub.com/­memcached/­memcached/­wikivitess.io/­docswww.warp10.io/­content/­02_Getting_started
DeveloperEsgynDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalThe Linux Foundation, PlanetScaleSenX
Initial release2015200320132015
Current release1.6.27, May 202415.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infoApache Version 2.0, commercial licenses availableOpen Source infoApache License 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 languageC++, JavaCGoJava
Server operating systemsLinuxFreeBSD
Linux
OS X
Unix
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesnoyes infowith proprietary extensionsno
APIs and other access methodsADO.NET
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infoproprietary syntaxyes infoWarpScript
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnone infoRepcached, a Memcached patch, provides this functionallityMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing SASL (Simple Authentication and Security Layer) protocolUsers with fine-grained authorization concept infono user groups or rolesMandatory use of cryptographic tokens, containing fine-grained authorizations

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
EsgynDBMemcachedVitessWarp 10
DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Why DDoS Threat Actors Are Shifting Their Tactics
15 March 2024, Infosecurity Magazine

Intel Continues To Demonstrate The Importance Of Software Optimizations: Clear Linux + Xeon Max Benchmarks
23 October 2023, Phoronix

Why Redis beats Memcached for caching
14 September 2017, InfoWorld

What are memcached servers, and why are they being used to launch record-setting DDoS attacks?
6 March 2018, GeekWire

Memcached DDoS: The biggest, baddest denial of service attacker yet
1 March 2018, ZDNet

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News

Time Series Databases Software market latest trends, CAGR, and forecast till 2026 | eSherpa Market Reports
13 April 2020, openPR

Time Series Intelligence Software Market Business Insights, Key Trend Analysis | Google, SAP, Azure Time Series ...
12 June 2024, Amoré

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

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.

Present your product here