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DBMS > Apache Drill vs. Google Cloud Bigtable vs. GridDB vs. TinkerGraph

System Properties Comparison Apache Drill vs. Google Cloud Bigtable vs. GridDB vs. TinkerGraph

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Time Series DBMSGraph DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websitedrill.apache.orgcloud.google.com/­bigtablegriddb.nettinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdrill.apache.org/­docscloud.google.com/­bigtable/­docsdocs.griddb.net
DeveloperApache Software FoundationGoogleToshiba Corporation
Initial release2012201520132009
Current release1.20.3, January 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen 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 languageC++Java
Server operating systemsLinux
OS X
Windows
hostedLinux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesnonoyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
TinkerPop 3
Supported programming languagesC++C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersnone
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenoyesyes
User concepts infoAccess controlDepending on the underlying data sourceAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseno
More information provided by the system vendor
Apache DrillGoogle Cloud BigtableGridDBTinkerGraph
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache DrillGoogle Cloud BigtableGridDBTinkerGraph
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