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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. Riak KV

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. Riak KV

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score4.49
Rank#79  Overall
#12  Document stores
Score4.44
Rank#80  Overall
#9  Key-value stores
Websitewww.esgyn.cncloud.google.com/­bigtablecloud.google.com/­datastore
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperEsgynGoogleGoogleOpenSource, formerly Basho Technologies
Initial release2015201520082009
Current release3.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaErlang
Server operating systemsLinuxhostedhostedLinux
OS X
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyes, details hereno
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.nononono
Secondary indexesyesnoyesrestricted
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnousing Google App EngineErlang
TriggersnonoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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 Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Security

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More resources
EsgynDBGoogle Cloud BigtableGoogle Cloud DatastoreRiak KV
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