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DBMS > Databend vs. GridGain vs. Hawkular Metrics

System Properties Comparison Databend vs. GridGain vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGridGain  Xexclude from comparisonHawkular Metrics  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 complexityGridGain is an in-memory computing platform, built on Apache IgniteHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMSColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.gridgain.comwww.hawkular.org
Technical documentationdocs.databend.comwww.gridgain.com/­docs/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperDatabend LabsGridGain Systems, Inc.Community supported by Red Hat
Initial release202120072014
Current release1.0.59, April 2023GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial, open sourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava, C++, .Net, Python, REST, SQLJava
Server operating systemshosted
Linux
macOS
Linux
OS X
Solaris
Windows
z/OS
Linux
OS X
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)yes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesRole-based access control
Security Hooks for custom implementations
no

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More resources
DatabendGridGainHawkular Metrics
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