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DBMS > Cachelot.io vs. CockroachDB vs. FatDB vs. Google Cloud Datastore vs. OpenTSDB

System Properties Comparison Cachelot.io vs. CockroachDB vs. FatDB vs. Google Cloud Datastore vs. OpenTSDB

Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonCockroachDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonOpenTSDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionIn-memory caching systemCockroachDB 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable Time Series DBMS based on HBase
Primary database modelKey-value storeRelational DBMSDocument store
Key-value store
Document storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#60  Key-value stores
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.68
Rank#146  Overall
#12  Time Series DBMS
Websitecachelot.iowww.cockroachlabs.comcloud.google.com/­datastoreopentsdb.net
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docsopentsdb.net/­docs/­build/­html/­index.html
DeveloperCockroach LabsFatCloudGooglecurrently maintained by Yahoo and other contributors
Initial release20152015201220082011
Current release23.1.1, May 2023
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoApache 2.0, commercial license availablecommercialcommercialOpen Source infoLGPL
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC#Java
Server operating systemsFreeBSD
Linux
OS X
Linux
macOS
Windows
WindowshostedLinux
Windows
Data schemeschema-freedynamic schemaschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyes, details herenumeric data for metrics, strings for tags
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
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)no
APIs and other access methodsMemcached protocolJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Telnet API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Erlang
Go
Java
Python
R
Ruby
Server-side scripts infoStored proceduresnonoyes infovia applicationsusing Google App Engineno
Triggersnonoyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal 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 infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using RAFTselectable replication factorMulti-source replication using Paxosselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate 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 infobased on HBase
Foreign keys infoReferential integritynoyesnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentnoyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnoRole-based access controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Cachelot.ioCockroachDBFatDBGoogle Cloud DatastoreOpenTSDB
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