DBMS > Faircom DB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Transwarp StellarDB

System Properties Comparison Faircom DB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Transwarp StellarDB

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Editorial information provided by DB-Engines
Name	Faircom DB formerly c-treeACE  Xexclude from comparison	Google Cloud Bigtable  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Transwarp StellarDB  Xexclude from comparison
Description	Native 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.	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	A distributed graph DBMS built for enterprise-level graph applications
Primary database model	Key-value store Relational DBMS	Key-value store Wide column store	Time Series DBMS	Graph DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.29 Rank #304   Overall #43   Key-value stores #136   Relational DBMS	Score 3.15 Rank #95   Overall #14   Key-value stores #8   Wide column stores	Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.07 Rank #371   Overall #39   Graph DBMS
Website	www.faircom.com/­products/­faircom-db	cloud.google.com/­bigtable	www.hawkular.org	www.transwarp.cn/­en/­product/­stellardb
Technical documentation	docs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html	cloud.google.com/­bigtable/­docs	www.hawkular.org/­hawkular-metrics/­docs/­user-guide
Developer	FairCom Corporation	Google	Community supported by Red Hat	Transwarp
Initial release	1979	2015	2014
Current release	V12, November 2020
License Commercial or Open Source	commercial Restricted, free version available	commercial	Open Source Apache 2.0	commercial
Cloud-based only Only available as a cloud service	no	yes	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	ANSI C, C++		Java
Server operating systems	AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs	hosted	Linux OS X Windows
Data scheme	schema free, schema optional, schema required, partial schema,	schema-free	schema-free
Typing predefined data types such as float or date	yes, ANSI SQL Types, JSON, typed binary structures	no	yes
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	no	no	no
Secondary indexes	yes	no	no
SQL Support of SQL	yes, ANSI SQL with proprietary extensions	no	no	SQL-like query language
APIs and other access methods	ADO.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)	HTTP REST	OpenCypher
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	Go Java Python Ruby
Server-side scripts Stored procedures	yes .Net, JavaScript, C/C++	no	no
Triggers	yes	no	yes via Hawkular Alerting
Partitioning methods Methods for storing different data on different nodes	File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning	Sharding	Sharding based on Cassandra	horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	yes, 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 zones	selectable replication factor based on Cassandra
MapReduce Offers an API for user-defined Map/Reduce methods	no	yes	no
Consistency concepts Methods to ensure consistency in a distributed system	Eventual 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)	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra
Foreign keys Referential integrity	yes	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	tunable from ACID to Eventually Consistent	Atomic single-row operations	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	Yes, tunable from durable to delayed durability to in-memory	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	no
User concepts Access control	Fine grained access rights according to SQL-standard with additional protections for files	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	no	yes
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More resources
	Faircom DB formerly c-treeACE	Google Cloud Bigtable	Hawkular Metrics	Transwarp StellarDB
Recent citations in the news	FairCom kicks off new era of database technology USA - English 10 November 2020, PR Newswire World's First Converged IIoT Hub to be Showcased at IoT Tech Expo 3 September 2021, Automation.com provided by Google News	Google's AI-First Strategy Brings Vector Support To Cloud Databases 1 March 2024, Forbes Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs 31 January 2022, InfoQ.com Google scales up Cloud Bigtable NoSQL database 27 January 2022, TechTarget Google introduces Cloud Bigtable managed NoSQL database to process data at scale 6 May 2015, VentureBeat Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database 6 May 2015, TechCrunch provided by Google News	Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News

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