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DBMS > EsgynDB vs. Google Cloud Datastore vs. Greenplum vs. IRONdb vs. JSqlDb

System Properties Comparison EsgynDB vs. Google Cloud Datastore vs. Greenplum vs. IRONdb vs. JSqlDb

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonIRONdb  Xexclude from comparisonJSqlDb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityJavaScript Query Language Database, stores JavaScript objects and primitives
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMSDocument store
Object oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score8.37
Rank#48  Overall
#30  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­datastoregreenplum.orgwww.circonus.com/solutions/time-series-database/jsqldb.org (offline)
Technical documentationcloud.google.com/­datastore/­docsdocs.greenplum.orgdocs.circonus.com/irondb/category/getting-started
DeveloperEsgynGooglePivotal Software Inc.Circonus LLC.Konrad von Backstrom
Initial release20152008200520172018
Current release7.0.0, September 2023V0.10.20, January 20180.8, December 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC and C++
Server operating systemsLinuxhostedLinuxLinuxLinux
macOS
Windows
Data schemeyesschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infotext, numeric, histogramsno
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 infosince Version 4.2nono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLyesSQL-like query language (GQL)yesSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
JavaScript
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App Engineyesyes, in Luafunctions in JavaScript
TriggersnoCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication using PaxosSource-replica replicationconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infousing RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
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)fine grained access rights according to SQL-standardno

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More resources
EsgynDBGoogle Cloud DatastoreGreenplumIRONdbJSqlDb
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