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DBMS > Google Cloud Datastore vs. HugeGraph vs. LevelDB vs. ObjectBox vs. Teradata

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. LevelDB vs. ObjectBox vs. Teradata

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonLevelDB  Xexclude from comparisonObjectBox  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesExtremely fast embedded database for small devices, IoT and MobileA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeGraph DBMSKey-value storeObject oriented DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
github.com/­google/­leveldbobjectbox.iowww.teradata.com
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.objectbox.iodocs.teradata.com
DeveloperGoogleBaiduGoogleObjectBox LimitedTeradata
Initial release20082018201120171984
Current release0.91.23, February 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoApache License 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C and C++
Server operating systemshostedLinux
macOS
Unix
Illumos
Linux
OS X
Windows
Android
iOS
Linux
macOS
Windows
hosted
Linux
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyesyes
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.nonononoyes
Secondary indexesyesyes infoalso supports composite index and range indexnoyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query language (GQL)nononoyes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Proprietary native API.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsnonoyes infoUDFs, stored procedures, table functions in parallel
TriggersCallbacks using the Google Apps Enginenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenonenoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenoneonline/offline synchronization between client and serverMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsnoyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreHugeGraphLevelDBObjectBoxTeradata
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More resources
Google Cloud DatastoreHugeGraphLevelDBObjectBoxTeradata
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