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DBMS > Databend vs. Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. STSdb

System Properties Comparison Databend vs. Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. STSdb

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonSTSdb  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 complexityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A widely adopted in-memory data gridKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument storeTime Series DBMSKey-value storeKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastorewww.hawkular.orghazelcast.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docs
DeveloperDatabend LabsGoogleCommunity supported by Red HatHazelcastSTS Soft SC
Initial release20212008201420082011
Current release1.0.59, April 20235.3.6, November 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJavaJavaC#
Server operating systemshosted
Linux
macOS
hostedLinux
OS X
Windows
All OS with a Java VMWindows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes infoprimitive types and user defined types (classes)
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.nononoyes infothe object must implement a serialization strategy
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-like query languageno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
Server-side scripts infoStored proceduresnousing Google App Enginenoyes infoEvent Listeners, Executor Servicesno
TriggersnoCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on CassandraShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole-based access controlno

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More resources
DatabendGoogle Cloud DatastoreHawkular MetricsHazelcastSTSdb
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