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DBMS > HugeGraph vs. Microsoft Azure Synapse Analytics vs. Vertica vs. XTDB

System Properties Comparison HugeGraph vs. Microsoft Azure Synapse Analytics vs. Vertica vs. XTDB

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerCloud 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.A general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelGraph DBMSRelational DBMSRelational DBMS infoColumn orientedDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­services/­synapse-analyticswww.vertica.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationhugegraph.apache.org/­docsdocs.microsoft.com/­azure/­synapse-analyticsvertica.com/­documentationwww.xtdb.com/­docs
DeveloperBaiduMicrosoftOpenText infopreviously Micro Focus and Hewlett PackardJuxt Ltd.
Initial release2018201620052019
Current release0.912.0.3, January 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoLimited community edition freeOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++Clojure
Server operating systemsLinux
macOS
Unix
hostedLinuxAll OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyesyesyesyes, extensible-data-notation format
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.nononono
Secondary indexesyes infoalso supports composite index and range indexyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.limited SQL, making use of Apache Calcite
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP REST
JDBC
Supported programming languagesGroovy
Java
Python
C#
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Clojure
Java
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsTransact SQLyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersnonoyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding, horizontal partitioninghorizontal partitioning, hierarchical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlUsers, roles and permissionsyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HugeGraphMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica infoOpenText™ Vertica™XTDB infoformerly named Crux
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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More resources
HugeGraphMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVertica infoOpenText™ Vertica™XTDB infoformerly named Crux
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