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DBMS > Apache Druid vs. etcd vs. Google Cloud Firestore vs. Hawkular Metrics vs. Microsoft Access

System Properties Comparison Apache Druid vs. etcd vs. Google Cloud Firestore vs. Hawkular Metrics vs. Microsoft Access

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA distributed reliable key-value storeCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeDocument storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score7.64
Rank#54  Overall
#5  Key-value stores
Score8.96
Rank#48  Overall
#8  Document stores
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Websitedruid.apache.orgetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorewww.hawkular.orgwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdruid.apache.org/­docs/­latest/­designetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestorewww.hawkular.org/­hawkular-metrics/­docs/­user-guidedeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation and contributorsGoogleCommunity supported by Red HatMicrosoft
Initial release2012201720141992
Current release29.0.1, April 20243.4, August 20191902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJavaC++
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Windows
Windows infoNot a real database server, but making use of DLLs
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesnoyes
SQL infoSupport of SQLSQL for queryingnononoyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP RESTADO.NET
DAO
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Go
Java
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyes, Firebase Rules & Cloud Functionsnoyes infosince Access 2010 using the ACE-engine
Triggersnoyes, watching key changesyes, with Cloud Functionsyes infovia Hawkular Alertingyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesnoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nono infoa simple user-level security was built in till version Access 2003

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More resources
Apache DruidetcdGoogle Cloud FirestoreHawkular MetricsMicrosoft Access
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