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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHazelcast  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.HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A widely adopted in-memory data gridBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelKey-value store
Wide column store
Document storeKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.55
Rank#243  Overall
#38  Document stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.43
Rank#260  Overall
#119  Relational DBMS
Websitecloud.google.com/­bigtablewww.harperdb.iohazelcast.comwww.postgres-xl.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docshazelcast.org/­imdg/­docswww.postgres-xl.org/­documentation
DeveloperGoogleHarperDBHazelcast
Initial release2015201720082014 infosince 2012, originally named StormDB
Current release3.1, August 20215.3.6, November 202310 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses 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 languageNode.jsJavaC
Server operating systemshostedLinux
OS X
All OS with a Java VMLinux
macOS
Data schemeschema-freedynamic schemaschema-freeyes
Typing infopredefined data types such as float or datenoyes infoJSON data typesyesyes
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 strategyyes infoXML type, but no XML query functionality
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like query languageyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.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++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes infoEvent Listeners, Executor Servicesuser defined functions
Triggersnonoyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsone or two-phase-commit; repeatable reads; read commitedACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
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)Access rights for users and rolesRole-based access controlfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableHarperDBHazelcastPostgres-XL
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