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DBMS > CrateDB vs. EsgynDB vs. Google Cloud Datastore vs. Greenplum

System Properties Comparison CrateDB vs. EsgynDB vs. Google Cloud Datastore vs. Greenplum

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparison
DescriptionDistributed Database based on LuceneEnterprise-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.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score8.37
Rank#48  Overall
#30  Relational DBMS
Websitecratedb.comwww.esgyn.cncloud.google.com/­datastoregreenplum.org
Technical documentationcratedb.com/­docscloud.google.com/­datastore/­docsdocs.greenplum.org
DeveloperCrateEsgynGooglePivotal Software Inc.
Initial release2013201520082005
Current release7.0.0, September 2023
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++, Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxhostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 4.2
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query language (GQL)yes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)Java Stored Proceduresusing Google App Engineyes
TriggersnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication between multi datacentersMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate 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 Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.nononono
User concepts infoAccess controlrights management via user accountsfine 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-standard
More information provided by the system vendor
CrateDBEsgynDBGoogle Cloud DatastoreGreenplum
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
CrateDBEsgynDBGoogle Cloud DatastoreGreenplum
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