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DBMS > BigObject vs. Faircom DB vs. Google Cloud Datastore vs. Ultipa

System Properties Comparison BigObject vs. Faircom DB vs. Google Cloud Datastore vs. Ultipa

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonUltipa  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Relational DBMS
Document storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#332  Overall
#147  Relational DBMS
Score0.19
Rank#311  Overall
#45  Key-value stores
#139  Relational DBMS
Score4.04
Rank#71  Overall
#12  Document stores
Score0.11
Rank#335  Overall
#32  Graph DBMS
Websitebigobject.iowww.faircom.com/­products/­faircom-dbcloud.google.com/­datastorewww.ultipa.com
Technical documentationdocs.bigobject.iodocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­datastore/­docswww.ultipa.com/­document
DeveloperBigObject, Inc.FairCom CorporationGoogleUltipa
Initial release2015197920082019
Current releaseV13, July 2024
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeyesschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes, 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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsSQL-like query language (GQL)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresLuayes info.Net, JavaScript, C/C++using Google App Engine
TriggersnoyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
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 methodsnonoyes 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 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 integrityyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BigObjectFaircom DB infoformerly c-treeACEGoogle Cloud DatastoreUltipa
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