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DBMS > 4D vs. Atos Standard Common Repository vs. EventStoreDB vs. TigerGraph vs. Vertica

System Properties Comparison 4D vs. Atos Standard Common Repository vs. EventStoreDB vs. TigerGraph vs. Vertica

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonEventStoreDB  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionApplication development environment with integrated database management systemHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksIndustrial-strength, open-source database solution built from the ground up for event sourcing.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSDocument store
Key-value store
Event StoreGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.80
Rank#111  Overall
#55  Relational DBMS
Score1.29
Rank#174  Overall
#1  Event Stores
Score1.92
Rank#143  Overall
#13  Graph DBMS
Score11.76
Rank#44  Overall
#28  Relational DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.eventstore.comwww.tigergraph.comwww.vertica.com
Technical documentationdeveloper.4d.comdevelopers.eventstore.comdocs.tigergraph.comvertica.com/­documentation
Developer4D, IncAtos Convergence CreatorsEvent Store LimitedOpenText infopreviously Micro Focus and Hewlett Packard
Initial release19842016201220172005
Current releasev20, April 2023170321.2, February 202112.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsOS X
Windows
LinuxLinux
Windows
LinuxLinux
Data schemeyesSchema and schema-less with LDAP viewsyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.yesyesnono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoclose to SQL 92noSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesnoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlUsers and groupsLDAP bind authenticationRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
4D infoformer name: 4th DimensionAtos Standard Common RepositoryEventStoreDBTigerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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4D infoformer name: 4th DimensionAtos Standard Common RepositoryEventStoreDBTigerGraphVertica infoOpenText™ Vertica™
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