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DBMS > Faircom DB vs. HEAVY.AI vs. ScyllaDB vs. Sphinx vs. Splice Machine

System Properties Comparison Faircom DB vs. HEAVY.AI vs. ScyllaDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonScyllaDB  Xexclude from comparisonSphinx  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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareCassandra and DynamoDB compatible wide column storeOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-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
Relational DBMSWide column storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score4.08
Rank#76  Overall
#5  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbgithub.com/­heavyai/­heavydb
www.heavy.ai
www.scylladb.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.heavy.aidocs.scylladb.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFairCom CorporationHEAVY.AI, Inc.ScyllaDBSphinx Technologies Inc.Splice Machine
Initial release19792016201520012014
Current releaseV12, November 20205.10, January 2022ScyllaDB Open Source 5.4.1, January 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2; enterprise edition availableOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageANSI C, C++C++ and CUDAC++C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema free, schema optional, schema required, partial schema,yesschema-freeyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesnoyes
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 indexesyesnoyes infocluster global secondary indicesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsyesSQL-like DML and DDL statements (CQL)SQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Thrift
Vega
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
All languages supporting JDBC/ODBC/Thrift
Python
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noyes, Luanoyes infoJava
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoRound robinShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared 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 replicationselectable replication factor infoRepresentation of geographical distribution of servers is possiblenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, 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 ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentnono infoAtomicity and isolation are supported for single operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoin-memory tablesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardAccess rights for users can be defined per objectnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Faircom DB infoformerly c-treeACEHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022ScyllaDBSphinxSplice Machine
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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More resources
Faircom DB infoformerly c-treeACEHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022ScyllaDBSphinxSplice Machine
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