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DBMS > CockroachDB vs. Google Cloud Datastore vs. GridGain vs. HBase

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. GridGain vs. HBase

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.cockroachlabs.comcloud.google.com/­datastorewww.gridgain.comhbase.apache.org
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlhbase.apache.org/­book.html
DeveloperCockroach LabsGoogleGridGain Systems, Inc.Apache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2015200820072008
Current release23.1.1, May 2023GridGain 8.5.12.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava, C++, .NetJava
Server operating systemsLinux
macOS
Windows
hostedLinux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Data schemedynamic schemaschema-freeyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyes, details hereyesoptions to bring your own types, AVRO
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLno
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
Java API
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnousing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infoCoprocessors in Java
TriggersnoCallbacks using the Google Apps Engineyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using Paxosyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yes
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 or Eventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDSingle row ACID (across millions of columns)
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.nonoyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
CockroachDBGoogle Cloud DatastoreGridGainHBase
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