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DBMS > Drizzle vs. Google Cloud Datastore vs. GridGain vs. LeanXcale

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. GridGain vs. LeanXcale

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonLeanXcale  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.leanxcale.com
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.html
DeveloperDrizzle project, originally started by Brian AkerGoogleGridGain Systems, Inc.LeanXcale
Initial release2008200820072015
Current release7.2.4, September 2012GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, C++, .Net
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, 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.noyes
Secondary indexesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infothrough Apache Derby
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
Java
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.noyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
DrizzleGoogle Cloud DatastoreGridGainLeanXcale
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