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DBMS > Cachelot.io vs. Faircom DB vs. GeoSpock vs. Google Cloud Datastore

System Properties Comparison Cachelot.io vs. Faircom DB vs. GeoSpock vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionIn-memory caching systemNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelKey-value storeKey-value store
Relational DBMS
Relational DBMSDocument store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#388  Overall
#62  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitecachelot.iowww.faircom.com/­products/­faircom-dbgeospock.comcloud.google.com/­datastore
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­datastore/­docs
DeveloperFairCom CorporationGeoSpockGoogle
Initial release201519792008
Current releaseV12, November 20202.0, September 2019
License infoCommercial or Open SourceOpen Source infoSimplified BSD Licensecommercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ANSI C, C++Java, Javascript
Server operating systemsFreeBSD
Linux
OS X
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedhosted
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesschema-free
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyesyes, details here
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 indexesnoyestemporal, categoricalyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsANSI SQL for query only (using Presto)SQL-like query language (GQL)
APIs and other access methodsMemcached protocolADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nousing Google App Engine
TriggersnoyesnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate 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.
Foreign keys infoReferential integritynoyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentnoYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Cachelot.ioFaircom DB infoformerly c-treeACEGeoSpockGoogle Cloud Datastore
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