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DBMS > Google Cloud Bigtable vs. GridGain vs. HarperDB vs. Postgres-XL

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. HarperDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonHarperDB  Xexclude from comparisonPostgres-XL  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 IgniteUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelKey-value store
Wide column store
Key-value store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsDocument 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
Score0.60
Rank#244  Overall
#38  Document stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitecloud.google.com/­bigtablewww.gridgain.comwww.harperdb.iowww.postgres-xl.org
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmldocs.harperdb.io/­docswww.postgres-xl.org/­documentation
DeveloperGoogleGridGain Systems, Inc.HarperDB
Initial release2015200720172014 infosince 2012, originally named StormDB
Current releaseGridGain 8.5.13.1, August 202110 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetNode.jsC
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Linux
macOS
Data schemeschema-freeyesdynamic schemayes
Typing infopredefined data types such as float or datenoyesyes infoJSON data typesyes
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.noyesnoyes infoXML type, but no XML query functionality
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like data manipulation statementsyes infodistributed, parallel query execution
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
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)Custom Functions infosince release 3.1user defined functions
Triggersnoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)yes infothe nodes on which a table resides can be defined
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDAtomic execution of specific operationsACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableGridGainHarperDBPostgres-XL
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