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DBMS > AnzoGraph DB vs. Faircom DB vs. GigaSpaces vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. Faircom DB vs. GigaSpaces vs. Spark SQL

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.faircom.com/­products/­faircom-dbwww.gigaspaces.comspark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.gigaspaces.com/­latest/­landing.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsFairCom CorporationGigaspaces TechnologiesApache Software Foundation
Initial release2018197920002014
Current release2.3, January 2021V12, November 202015.5, September 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infoRestricted, free version availableOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++Java, C++, .NetScala
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema free, schema optional, schema required, partial schema,schema-freeyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesnoyesyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes, ANSI SQL with proprietary extensionsSQL-99 for query and DML statementsSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC++
Java
Python
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C++
Java
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++yesno
Triggersnoyesyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes, 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 infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infoMap-Reduce pattern can be built with XAP task executors
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integrityno infonot needed in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, 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.yesyesyesno
User concepts infoAccess controlAccess rights for users and rolesFine grained access rights according to SQL-standard with additional protections for filesRole-based access controlno

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More resources
AnzoGraph DBFaircom DB infoformerly c-treeACEGigaSpacesSpark SQL
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