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DBMS > RavenDB vs. Stardog vs. TDengine vs. Transbase vs. Vertica

System Properties Comparison RavenDB vs. Stardog vs. TDengine vs. Transbase vs. Vertica

Editorial information provided by DB-Engines
NameRavenDB  Xexclude from comparisonStardog  Xexclude from comparisonTDengine  Xexclude from comparisonTransbase  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTime Series DBMS and big data platformA resource-optimized, high-performance, universally applicable RDBMSCloud 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 modelDocument storeGraph DBMS
RDF store
Time Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#101  Overall
#18  Document stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteravendb.netwww.stardog.comgithub.com/­taosdata/­TDengine
tdengine.com
www.transaction.de/­en/­products/­transbase.htmlwww.vertica.com
Technical documentationravendb.net/­docsdocs.stardog.comdocs.tdengine.comwww.transaction.de/­en/­products/­transbase/­features.htmlvertica.com/­documentation
DeveloperHibernating RhinosStardog-UnionTDEngine, previously Taos DataTransaction Software GmbHOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20102010201919872005
Current release5.4, July 20227.3.0, May 20203.0, August 2022Transbase 8.3, 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoAGPL V3, also commercial editions availablecommercial infofree development licensecommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaCC and C++C++
Server operating systemsLinux
macOS
Raspberry Pi
Windows
Linux
macOS
Windows
Linux
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Linux
Data schemeschema-freeschema-free and OWL/RDFS-schema supportyesyesYes, 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 datenoyesyesyesyes
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.no infoImport/export of XML data possiblenonono
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query language (RQL)Yes, compatible with all major SQL variants through dedicated BI/SQL ServerStandard SQL with extensions for time-series applicationsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
JDBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functions and aggregates, HTTP Server extensions in Javanoyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infovia event handlersyes, via alarm monitoringyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication in HA-ClusteryesSource-replica replicationMulti-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 methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency in HA-ClusterImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID, Cluster-wide transaction availableACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAuthorization levels configured per client per databaseAccess rights for users and rolesyesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
RavenDBStardogTDengineTransbaseVertica infoOpenText™ Vertica™
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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Comprehensive Comparison Between TDengine and TimescaleDB
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31 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
RavenDBStardogTDengineTransbaseVertica infoOpenText™ Vertica™
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