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DBMS > Faircom DB vs. Google Cloud Bigtable vs. TimescaleDB

System Properties Comparison Faircom DB vs. Google Cloud Bigtable vs. TimescaleDB

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Relational DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.18
Rank#351  Overall
#53  Key-value stores
#148  Relational DBMS
Score5.44
Rank#76  Overall
#9  Key-value stores
#7  Wide column stores
Score4.52
Rank#88  Overall
#5  Time Series DBMS
Websitewww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtablewww.timescale.com
Technical documentationlearn.faircomcorp.com/­developers/­documentation_directorycloud.google.com/­bigtable/­docsdocs.timescale.com
DeveloperFairCom CorporationGoogleTimescale
Initial release197920152017
Current releaseV12, November 20202.6.0, February 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Windows
Data schemeschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresnonumerics, 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 indexesyesnoyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard
More information provided by the system vendor
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableTimescaleDB
Specific characteristicsAchieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» more
Competitive advantagesTop Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» more
Typical application scenariosReal-time transaction processing solutions leverage FairCom DB because its NoSQL...
» more
Key customersMicrosoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» more
Market metricsFrom banking and financial transactions, transportation, warehouse automation, package...
» more
Licensing and pricing modelsJust as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» more

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More resources
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableTimescaleDB
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