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DBMS > Faircom DB vs. HBase vs. Splice Machine

System Properties Comparison Faircom DB vs. HBase vs. Splice Machine

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHBase  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.Wide-column store based on Apache Hadoop and on concepts of BigTableOpen-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
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#298  Overall
#42  Key-value stores
#137  Relational DBMS
Score31.60
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbhbase.apache.orgsplicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhbase.apache.org/­book.htmlsplicemachine.com/­how-it-works
DeveloperFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSplice Machine
Initial release197920082014
Current releaseV12, November 20202.3.4, January 20213.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,schema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresoptions to bring your own types, AVROyes
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoyes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoCoprocessors in Javayes infoJava
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShared 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).Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, 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 or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentYes, 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.yesyesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEHBaseSplice Machine
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