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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonVoltDB  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelKey-value store
Wide column store
Relational DBMSGraph DBMSRelational 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitecloud.google.com/­bigtablehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
www.voltdb.com
Technical documentationcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docsdocs.voltdb.com
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookBaiduVoltDB Inc.
Initial release2015201220182010
Current release3.1.3, April 20220.911.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava, C++
Server operating systemshostedAll OS with a Java VMLinux
macOS
Unix
Linux
OS X infofor development
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.nono
Secondary indexesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes infoonly a subset of SQL 99
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Groovy
Java
Python
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsJava
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducevia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesUsers, roles and permissionsUsers and roles with access to stored procedures

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More resources
Google Cloud BigtableHiveHugeGraphVoltDB
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