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DBMS > Apache Druid vs. CockroachDB vs. Faircom DB vs. Microsoft Access

System Properties Comparison Apache Druid vs. CockroachDB vs. Faircom DB vs. Microsoft Access

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCockroachDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.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
Relational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websitedruid.apache.orgwww.cockroachlabs.comwww.faircom.com/­products/­faircom-dbwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdruid.apache.org/­docs/­latest/­designwww.cockroachlabs.com/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation and contributorsCockroach LabsFairCom CorporationMicrosoft
Initial release2012201519791992
Current release29.0.1, April 202424.1.0, May 2024V12, November 20201902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0, commercial license availablecommercial infoRestricted, free version availablecommercial infoBundled with Microsoft Office
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 languageJavaGoANSI C, C++C++
Server operating systemsLinux
OS X
Unix
Linux
macOS
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Windows infoNot a real database server, but making use of DLLs
Data schemeyes infoschema-less columns are supporteddynamic schemaschema free, schema optional, schema required, partial schema,yes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyes, wire compatible with PostgreSQLyes, ANSI SQL with proprietary extensionsyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++yes infosince Access 2010 using the ACE-engine
Triggersnonoyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using RAFTyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
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
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually ConsistentACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes 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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlFine grained access rights according to SQL-standard with additional protections for filesno infoa simple user-level security was built in till version Access 2003

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More resources
Apache DruidCockroachDBFaircom DB infoformerly c-treeACEMicrosoft Access
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