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

DBMS > Ehcache vs. JanusGraph vs. KeyDB vs. Microsoft Azure Table Storage

System Properties Comparison Ehcache vs. JanusGraph vs. KeyDB vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value storeGraph DBMSKey-value storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitewww.ehcache.orgjanusgraph.orggithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationwww.ehcache.org/­documentationdocs.janusgraph.orgdocs.keydb.dev
DeveloperTerracotta Inc, owned by Software AGLinux Foundation; originally developed as Titan by AureliusEQ Alpha Technology Ltd.Microsoft
Initial release2009201720192012
Current release3.10.0, March 20220.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Unix
Windows
Linuxhosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesnoyesyes infoby using the Redis Search moduleno
SQL infoSupport of SQLnononono
APIs and other access methodsJCacheJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Proprietary protocol infoRESP - REdis Serialization ProtocoRESTful HTTP API
Supported programming languagesJavaClojure
Java
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyesLuano
Triggersyes infoCache Event Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta Serveryes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)ShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServeryesMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceACIDOptimistic locking, atomic execution of commands blocks and scriptsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoUser authentification and security via Rexster Graph Serversimple password-based access control and ACLAccess rights based on private key authentication or shared access signatures

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
EhcacheJanusGraph infosuccessor of TitanKeyDBMicrosoft Azure Table Storage
Recent citations in the news

Scaling Australia's Most Popular Online News Sites with Ehcache
6 December 2010, InfoQ.com

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

DZone Coding Java JBoss 5 to 7 in 11 steps
9 January 2014, DZone

provided by Google News

Database Deep Dives: JanusGraph
8 August 2019, IBM

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

provided by Google News

Oh, snap! Snap snaps up database developer KeyDB
12 May 2022, TechCrunch

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, Microsoft

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Microsoft open-sources Garnet cache-store -- a Redis rival?
19 March 2024, The Stack

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

Inside Azure File Storage
7 October 2015, azure.microsoft.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News



Share this page

Featured Products

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

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

Present your product here