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DBMS > CockroachDB vs. Google Cloud Datastore vs. HarperDB vs. Ingres

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. HarperDB vs. Ingres

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonIngres  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 PlatformUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Well established RDBMS
Primary database modelRelational DBMSDocument storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.60
Rank#244  Overall
#38  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websitewww.cockroachlabs.comcloud.google.com/­datastorewww.harperdb.iowww.actian.com/­databases/­ingres
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docsdocs.harperdb.io/­docsdocs.actian.com/­ingres
DeveloperCockroach LabsGoogleHarperDBActian Corporation
Initial release2015200820171974 infooriginally developed at University Berkely in early 1970s
Current release24.1.0, May 20243.1, August 202111.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialcommercial infofree community edition availablecommercial
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 languageGoNode.jsC
Server operating systemsLinux
macOS
Windows
hostedLinux
OS X
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemedynamic schemaschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyes, details hereyes infoJSON data typesyes
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.nononono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query language (GQL)SQL-like data manipulation statementsyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresnousing Google App EngineCustom Functions infosince release 3.1yes
TriggersnoCallbacks using the Google Apps Enginenoyes
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 RAFTShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using Paxosyes infothe nodes on which a table resides can be definedIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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
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 TransactionsAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesfine grained access rights according to SQL-standard

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More resources
CockroachDBGoogle Cloud DatastoreHarperDBIngres
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