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DBMS > Google BigQuery vs. GreptimeDB vs. Hazelcast vs. Linter

System Properties Comparison Google BigQuery vs. GreptimeDB vs. Hazelcast vs. Linter

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGreptimeDB  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesAn open source Time Series DBMS built for increased scalability, high performance and efficiencyA widely adopted in-memory data gridRDBMS for high security requirements
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score0.06
Rank#352  Overall
#33  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websitecloud.google.com/­bigquerygreptime.comhazelcast.comlinter.ru
Technical documentationcloud.google.com/­bigquery/­docsdocs.greptime.comhazelcast.org/­imdg/­docs
DeveloperGoogleGreptime Inc.Hazelcastrelex.ru
Initial release2010202220081990
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustJavaC and C++
Server operating systemshostedAndroid
Docker
FreeBSD
Linux
macOS
Windows
All OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesyesSQL-like query languageyes
APIs and other access methodsRESTful HTTP/JSON APIgRPC
HTTP API
JDBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Erlang
Go
Java
JavaScript
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptPythonyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnoyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataone or two-phase-commit; repeatable reads; read commitedACID
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.noyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Simple rights management via user accountsRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Google BigQueryGreptimeDBHazelcastLinter
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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More resources
Google BigQueryGreptimeDBHazelcastLinter
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