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DBMS > Graph Engine vs. Informix vs. Spark SQL vs. VelocityDB

System Properties Comparison Graph Engine vs. Informix vs. Spark SQL vs. VelocityDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataSpark SQL is a component on top of 'Spark Core' for structured data processingA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelGraph DBMS
Key-value store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSGraph DBMS
Object oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#354  Overall
#37  Graph DBMS
#15  Object oriented DBMS
Websitewww.graphengine.iowww.ibm.com/­products/­informixspark.apache.org/­sqlvelocitydb.com
Technical documentationwww.graphengine.io/­docs/­manualinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.apache.org/­docs/­latest/­sql-programming-guide.htmlvelocitydb.com/­UserGuide
DeveloperMicrosoftIBM, 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.Apache Software FoundationVelocityDB Inc
Initial release2010198420142011
Current release14.10.FC5, November 20203.5.0 ( 2.13), September 20237.x
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infofree developer edition availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC, C++ and JavaScalaC#
Server operating systems.NETAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Any that supports .NET
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIJDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
.Net
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Server-side scripts infoStored proceduresyesyesnono
TriggersnoyesnoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlUsers with fine-grained authentication, authorization, and auditing controlsnoBased on Windows Authentication

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More resources
Graph Engine infoformer name: TrinityInformixSpark SQLVelocityDB
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