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DBMS > Apache Kylin vs. Google Cloud Datastore vs. Oracle NoSQL vs. QuestDB

System Properties Comparison Apache Kylin vs. Google Cloud Datastore vs. Oracle NoSQL vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesA high performance open source SQL database for time series data
Primary database modelRelational DBMSDocument storeDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitekylin.apache.orgcloud.google.com/­datastorewww.oracle.com/­database/­nosql/­technologies/­nosqlquestdb.io
Technical documentationkylin.apache.org/­docscloud.google.com/­datastore/­docsdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlquestdb.io/­docs
DeveloperApache Software Foundation, originally contributed from eBay IncGoogleOracleQuestDB Technology Inc
Initial release2015200820112014
Current release3.1.0, July 202024.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava (Zero-GC), C++, Rust
Server operating systemsLinuxhostedLinux
Solaris SPARC/x86
Linux
macOS
Windows
Data schemeyesschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.yes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes, details hereoptionalyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like query language (GQL)SQL-like DML and DDL statementsSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
Go
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresusing Google App Enginenono
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosElectable source-replica replication per shard. Support distributed global deployment with Multi-region table featureSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowwith Hadoop integrationno
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
Immediate Consistency infodepending on configuration
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsconfigurable infoACID within a storage node (=shard)ACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infooff heap cacheyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles
More information provided by the system vendor
Apache KylinGoogle Cloud DatastoreOracle NoSQLQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache KylinGoogle Cloud DatastoreOracle NoSQLQuestDB
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