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DBMS > Apache Phoenix vs. CockroachDB vs. Faircom EDGE vs. Sqrrl

System Properties Comparison Apache Phoenix vs. CockroachDB vs. Faircom EDGE vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCockroachDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCockroachDB 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.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Document store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Websitephoenix.apache.orgwww.cockroachlabs.comwww.faircom.com/­products/­faircom-edgesqrrl.com
Technical documentationphoenix.apache.orgwww.cockroachlabs.com/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperApache Software FoundationCockroach LabsFairCom CorporationAmazon infooriginally Sqrrl Data, Inc.
Initial release2014201519792012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201924.1.0, May 2024V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0, commercial license availablecommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoANSI C, C++Java
Server operating systemsLinux
Unix
Windows
Linux
macOS
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesdynamic schemaFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes, wire compatible with PostgreSQLyes infoANSI SQL queriesno
APIs and other access methodsJDBCJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functionsnoyes info.Net, JavaScript, C/C++no
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal 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 infoCustomizable business rules for partitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using RAFTyes infoSynchronous and asynchronous realtime replication based on transaction logsselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-based access controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache PhoenixCockroachDBFaircom EDGE infoformerly c-treeEDGESqrrl
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