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DBMS > Cachelot.io vs. CrateDB vs. Google Cloud Datastore vs. Yanza

System Properties Comparison Cachelot.io vs. CrateDB vs. Google Cloud Datastore vs. Yanza

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionIn-memory caching systemDistributed Database based on LuceneAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS for IoT Applications
Primary database modelKey-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#388  Overall
#62  Key-value stores
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitecachelot.iocratedb.comcloud.google.com/­datastoreyanza.com
Technical documentationcratedb.com/­docscloud.google.com/­datastore/­docs
DeveloperCrateGoogleYanza
Initial release2015201320082015
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Sourcecommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsFreeBSD
Linux
OS X
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedWindows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or datenoyesyes, details hereno
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 indexesnoyesyesno
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language (GQL)no
APIs and other access methodsMemcached protocolADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
.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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresnouser defined functions (Javascript)using Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Read-after-write consistency on record level
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
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnorights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Cachelot.ioCrateDBGoogle Cloud DatastoreYanza
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