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DBMS > Apache Impala vs. Faircom DB vs. TimescaleDB

System Properties Comparison Apache Impala vs. Faircom DB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websiteimpala.apache.orgwww.faircom.com/­products/­faircom-dbwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationTimescale
Initial release201319792017
Current release4.1.0, June 2022V12, November 20202.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++C
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesYes, 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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaFaircom DB infoformerly c-treeACETimescaleDB
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
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Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

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Visualizing IoT Data at Scale With Hopara and TimescaleDB
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Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

provided by Google News



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