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DBMS > Apache Impala vs. Apache Phoenix vs. Datomic vs. Faircom DB

System Properties Comparison Apache Impala vs. Apache Phoenix vs. Datomic vs. Faircom DB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseDatomic 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.
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteimpala.apache.orgphoenix.apache.orgwww.datomic.comwww.faircom.com/­products/­faircom-db
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationCognitectFairCom Corporation
Initial release2013201420121979
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20191.0.6735, June 2023V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infolimited edition freecommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava, ClojureANSI C, C++
Server operating systemsLinuxLinux
Unix
Windows
All OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesschema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI SQL Types, JSON, typed binary structures
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes, ANSI SQL with proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBCRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Clojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes infoTransaction Functionsyes info.Net, JavaScript, C/C++
TriggersnonoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
none 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).
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDtunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoFine grained access rights according to SQL-standard with additional protections for files

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More resources
Apache ImpalaApache PhoenixDatomicFaircom DB infoformerly c-treeACE
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