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DBMS > Google Cloud Datastore vs. Kinetica vs. Newts vs. QuestDB vs. searchxml

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Newts vs. QuestDB vs. searchxml

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonNewts  Xexclude from comparisonQuestDB  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsTime Series DBMS based on CassandraA high performance open source SQL database for time series dataDBMS for structured and unstructured content wrapped with an application server
Primary database modelDocument storeRelational DBMSTime Series DBMSTime Series DBMSNative XML DBMS
Search engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websitecloud.google.com/­datastorewww.kinetica.comopennms.github.io/­newtsquestdb.iowww.searchxml.net/­category/­products
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comgithub.com/­OpenNMS/­newts/­wikiquestdb.io/­docswww.searchxml.net/­support/­handouts
DeveloperGoogleKineticaOpenNMS GroupQuestDB Technology Incinformationpartners gmbh
Initial release20082012201420142015
Current release7.1, August 20211.0
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaJava (Zero-GC), C++, RustC++
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
macOS
Windows
Windows
Data schemeschema-freeyesschema-freeyes infoschema-free via InfluxDB Line Protocolschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.nonononoyes
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoSQL with time-series extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP REST
Java API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnonoyes infoon the application server
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandrahorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationselectable replication factor infobased on CassandraSource-replica replication with eventual consistencyyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID for single-table writesmultiple readers, single writer
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.noyes infoGPU vRAM or System RAMnoyes infothrough memory mapped filesno
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 on table levelnoDomain, group and role-based access control at the document level and for application services
More information provided by the system vendor
Google Cloud DatastoreKineticaNewtsQuestDBsearchxml
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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