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DBMS > Google Cloud Bigtable vs. HarperDB vs. Hive vs. HugeGraph

System Properties Comparison Google Cloud Bigtable vs. HarperDB vs. Hive vs. HugeGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  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.Ultra-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.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMS
Primary database modelKey-value store
Wide column store
Document storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitecloud.google.com/­bigtablewww.harperdb.iohive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperGoogleHarperDBApache Software Foundation infoinitially developed by FacebookBaidu
Initial release2015201720122018
Current release3.1, August 20213.1.3, April 20220.9
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsJavaJava
Server operating systemshostedLinux
OS X
All OS with a Java VMLinux
macOS
Unix
Data schemeschema-freedynamic schemayesyes
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.nonono
Secondary indexesnoyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like DML and DDL statementsno
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
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
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
C++
Java
PHP
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobs
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
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 definedselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoquery execution via MapReducevia hugegraph-spark
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsnoACID
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesAccess rights for users, groups and rolesUsers, roles and permissions

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More resources
Google Cloud BigtableHarperDBHiveHugeGraph
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