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DBMS > FatDB vs. Informix vs. RavenDB vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison FatDB vs. Informix vs. RavenDB vs. Spark SQL vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInformix  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument store
Key-value store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBDocument storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.ibm.com/­products/­informixravendb.netspark.apache.org/­sqlvictoriametrics.com
Technical documentationinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
ravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperFatCloudIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Hibernating RhinosApache Software FoundationVictoriaMetrics
Initial release20121984201020142018
Current release14.10.FC5, November 20205.4, July 20223.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
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.
Implementation languageC#C, C++ and JavaC#ScalaGo
Server operating systemsWindowsAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesnoyes
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 indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query language (RQL)SQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesyesnono
Triggersyes infovia applicationsyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replicationnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, Cluster-wide transaction availablenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsUsers with fine-grained authentication, authorization, and auditing controlsAuthorization levels configured per client per databaseno

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FatDBInformixRavenDBSpark SQLVictoriaMetrics
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