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DBMS > Apache Druid vs. Datomic vs. Faircom DB vs. Hawkular Metrics

System Properties Comparison Apache Druid vs. Datomic vs. Faircom DB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store
Relational DBMS
Time Series 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Websitedruid.apache.orgwww.datomic.comwww.faircom.com/­products/­faircom-dbwww.hawkular.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software Foundation and contributorsCognitectFairCom CorporationCommunity supported by Red Hat
Initial release2012201219792014
Current release29.0.1, April 20241.0.6735, June 2023V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureANSI C, C++Java
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingnoyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP REST
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes info.Net, JavaScript, C/C++no
TriggersnoBy using transaction functionsyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoFine grained access rights according to SQL-standard with additional protections for filesno

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More resources
Apache DruidDatomicFaircom DB infoformerly c-treeACEHawkular Metrics
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