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DBMS > Google Cloud Bigtable vs. HugeGraph vs. Teradata Aster vs. VoltDB

System Properties Comparison Google Cloud Bigtable vs. HugeGraph vs. Teradata Aster vs. VoltDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonTeradata Aster  Xexclude from comparisonVoltDB  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMSPlatform for big data analytics on multistructured data sources and typesDistributed 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
Graph DBMSRelational 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
www.voltdb.com
Technical documentationcloud.google.com/­bigtable/­docshugegraph.apache.org/­docsdocs.voltdb.com
DeveloperGoogleBaiduTeradataVoltDB Inc.
Initial release2015201820052010
Current release0.911.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++
Server operating systemshostedLinux
macOS
Unix
LinuxLinux
OS X infofor development
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
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.nonoyes infoin Aster File Store
Secondary indexesnoyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLnonoyesyes infoonly a subset of SQL 99
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
OLE DB
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C
C#
C++
Java
Python
R
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsR packagesJava
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesvia hugegraph-sparkyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoedges in graphnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID 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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsfine grained access rights according to SQL-standardUsers and roles with access to stored procedures

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More resources
Google Cloud BigtableHugeGraphTeradata AsterVoltDB
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