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DBMS > EXASOL vs. Microsoft Azure SQL Database vs. TigerGraph vs. Vertica

System Properties Comparison EXASOL vs. Microsoft Azure SQL Database vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTigerGraph  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Database as a Service offering with high compatibility to Microsoft SQL ServerA 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 DBMSRelational DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.exasol.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.tigergraph.comwww.vertica.com
Technical documentationwww.exasol.com/­resourcesdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.tigergraph.comvertica.com/­documentation
DeveloperExasolMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2000201020172005
Current releaseV1212.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono 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 languageC++C++C++
Server operating systemshostedLinuxLinux
Data schemeyesyesyesYes, 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 dateyesyesyesyes
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.noyesnono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyesSQL-like query language (GSQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
JDBC
ODBC
WebSocket
ADO.NET
JDBC
ODBC
GSQL (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 languagesJava
Lua
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsTransact SQLyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with always 3 replicas availableMulti-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 methodsyes infoHadoop integrationnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EXASOLMicrosoft Azure SQL Database infoformerly SQL AzureTigerGraphVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
EXASOLMicrosoft Azure SQL Database infoformerly SQL AzureTigerGraphVertica infoOpenText™ Vertica™
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