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DBMS > Apache Drill vs. Apache Phoenix vs. Faircom DB vs. Splice Machine

System Properties Comparison Apache Drill vs. Apache Phoenix vs. Faircom DB vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache Phoenix  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageA scale-out RDBMS with evolutionary schema built on Apache HBaseNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitedrill.apache.orgphoenix.apache.orgwww.faircom.com/­products/­faircom-dbsplicemachine.com
Technical documentationdrill.apache.org/­docsphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationApache Software FoundationFairCom CorporationSplice Machine
Initial release2012201419792014
Current release1.20.3, January 20235.0-HBase2, July 2018 and 4.15-HBase1, December 2019V12, November 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++Java
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema 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 indexesnoyesyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyesyes, ANSI SQL with proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes info.Net, JavaScript, C/C++yes infoJava
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesHadoop integrationnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentDepending on the underlying data sourceyesYes, 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.Depending on the underlying data sourceyesyesyes
User concepts infoAccess controlDepending on the underlying data sourceAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DrillApache PhoenixFaircom DB infoformerly c-treeACESplice Machine
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