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DBMS > Faircom DB vs. Google Cloud Bigtable vs. MarkLogic vs. Splice Machine

System Properties Comparison Faircom DB vs. Google Cloud Bigtable vs. MarkLogic vs. Splice Machine

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Operational and transactional Enterprise NoSQL databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Key-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtablewww.marklogic.comsplicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docsdocs.marklogic.comsplicemachine.com/­how-it-works
DeveloperFairCom CorporationGoogleMarkLogic Corp.Splice Machine
Initial release1979201520012014
Current releaseV12, November 202011.0, December 20223.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercial inforestricted free version is availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,schema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresnoyesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoyes infoSQL92yes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noyes infovia XQuery or JavaScriptyes infoJava
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Internal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, with Range Indexesyes
User concepts infoAccess controlFine 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)Role-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standard

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Faircom DB infoformerly c-treeACEGoogle Cloud BigtableMarkLogicSplice Machine
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