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DBMS > Google Cloud Bigtable vs. GridGain vs. TerminusDB vs. Vitess

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. TerminusDB vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationshipsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value store
Wide column store
Key-value store
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsDocument store
RDF store
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitecloud.google.com/­bigtablewww.gridgain.comterminusdb.comvitess.io
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmlterminusdb.github.io/­terminusdb/­#vitess.io/­docs
DeveloperGoogleGridGain Systems, Inc.DataChemist Ltd.The Linux Foundation, PlanetScale
Initial release2015200720182013
Current releaseGridGain 8.5.111.0.0, January 202315.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V3Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetProlog, RustGo
Server operating systemshostedLinux
OS X
Solaris
Windows
LinuxDocker
Linux
macOS
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyesno
Secondary indexesnoyesyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like query language (WOQL)yes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
JavaScript
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yesyes infoproprietary syntax
Triggersnoyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingGraph PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)Journaling StreamsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoin-memory journalingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsRole-based access controlUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud BigtableGridGainTerminusDB infoformer name was DataChemistVitess
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