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DBMS > Apache Druid vs. Ehcache vs. QuestDB vs. Stardog

System Properties Comparison Apache Druid vs. Ehcache vs. QuestDB vs. Stardog

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEhcache  Xexclude from comparisonQuestDB  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted Java cache with tiered storage optionsA high performance open source SQL database for time series dataEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeTime Series DBMSGraph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitedruid.apache.orgwww.ehcache.orgquestdb.iowww.stardog.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ehcache.org/­documentationquestdb.io/­docsdocs.stardog.com
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGQuestDB Technology IncStardog-Union
Initial release2012200920142010
Current release29.0.1, April 20243.10.0, March 20227.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava (Zero-GC), C++, RustJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
macOS
Windows
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyes infoschema-free via InfluxDB Line Protocolschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoImport/export of XML data possible
Secondary indexesyesnonoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL for queryingnoSQL with time-series extensionsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCacheHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoCache Event Listenersnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoby using Terracotta Serverhorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby using Terracotta ServerSource-replica replication with eventual consistencyMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourceACID for single-table writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped filesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users and roles
More information provided by the system vendor
Apache DruidEhcacheQuestDBStardog
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache DruidEhcacheQuestDBStardog
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