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DBMS > AgensGraph vs. EsgynDB vs. Google Cloud Datastore vs. Greenplum vs. Impala

System Properties Comparison AgensGraph vs. EsgynDB vs. Google Cloud Datastore vs. Greenplum vs. Impala

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonImpala  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLEnterprise-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.Analytic DBMS for Hadoop
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#312  Overall
#30  Graph DBMS
#140  Relational DBMS
Score0.23
Rank#281  Overall
#130  Relational DBMS
Score4.84
Rank#76  Overall
#11  Document stores
Score13.96
Rank#42  Overall
#26  Relational DBMS
Score18.46
Rank#39  Overall
#24  Relational DBMS
Websitebitnine.netwww.esgyn.cncloud.google.com/­datastoregreenplum.orgwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docsdocs.greenplum.orgdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperBitnine Global Inc.EsgynGooglePivotal Software Inc.Cloudera
Initial release20162015200820052013
Current release2.1, December 20186.7.1, April 20204.0.0, July 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++, JavaC++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinuxLinux
Data schemedepending on used data modelyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nononoyes infosince Version 4.2no
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesyesSQL-like query language (GQL)yesSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
All languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresyesJava Stored Proceduresusing Google App Engineyesyes infouser defined functions and integration of map-reduce
TriggersnonoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersMulti-source replication using PaxosSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine 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-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos

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More resources
AgensGraphEsgynDBGoogle Cloud DatastoreGreenplumImpala
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