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DBMS > EsgynDB vs. Geode vs. Google Cloud Bigtable vs. Google Cloud Datastore

System Properties Comparison EsgynDB vs. Geode vs. Google Cloud Bigtable vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle'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 Platform
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.47
Rank#76  Overall
#12  Document stores
Websitewww.esgyn.cngeode.apache.orgcloud.google.com/­bigtablecloud.google.com/­datastore
Technical documentationgeode.apache.org/­docscloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docs
DeveloperEsgynOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleGoogle
Initial release2015200220152008
Current release1.1, February 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava
Server operating systemsLinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedhosted
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, details here
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 indexesyesnonoyes
SQL infoSupport of SQLyesSQL-like query language (OQL)noSQL-like query language (GQL)
APIs and other access methodsADO.NET
JDBC
ODBC
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsnousing Google App Engine
Triggersnoyes infoCache Event ListenersnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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.
Foreign keys infoReferential integrityyesnonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights per client and object definableAccess 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)

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More resources
EsgynDBGeodeGoogle Cloud BigtableGoogle Cloud Datastore
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