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DBMS > Databend vs. Faircom DB vs. Hawkular Metrics vs. KairosDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Databend vs. Faircom DB vs. Hawkular Metrics vs. KairosDB vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKairosDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Distributed Time Series DBMS based on Cassandra or H2Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.62
Rank#239  Overall
#20  Time Series DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.faircom.com/­products/­faircom-dbwww.hawkular.orggithub.com/­kairosdb/­kairosdbazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.databend.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidekairosdb.github.iodocs.microsoft.com/­azure/­synapse-analytics
DeveloperDatabend LabsFairCom CorporationCommunity supported by Red HatMicrosoft
Initial release20211979201420132016
Current release1.0.59, April 2023V12, November 20201.2.2, November 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustANSI C, C++JavaJavaC++
Server operating systemshosted
Linux
macOS
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Linux
OS X
Windows
hosted
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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.nonononono
Secondary indexesnoyesnonoyes
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsnonoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP RESTGraphite protocol
HTTP REST
Telnet API
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
Java
Python
Ruby
Java
JavaScript infoNode.js
PHP
Python
C#
Java
PHP
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nonoTransact SQL
Triggersnoyesyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infobased on CassandraSharding infobased on CassandraSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable replication factor infobased on Cassandraselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayestunable from ACID to Eventually ConsistentnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesFine grained access rights according to SQL-standard with additional protections for filesnosimple password-based access controlyes

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More resources
DatabendFaircom DB infoformerly c-treeACEHawkular MetricsKairosDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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