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DBMS > Apache IoTDB vs. SurrealDB vs. Vertica vs. Yaacomo

System Properties Comparison Apache IoTDB vs. SurrealDB vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonSurrealDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA fully ACID transactional, developer-friendly, multi-model DBMSCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSDocument store
Graph DBMS
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteiotdb.apache.orgsurrealdb.comwww.vertica.comyaacomo.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsurrealdb.com/­docsvertica.com/­documentation
DeveloperApache Software FoundationSurrealDB LtdOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release2018202220052009
Current release1.1.0, April 2023v1.5.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenonono 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 languageJavaRustC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Windows
LinuxAndroid
Linux
Windows
Data schemeyesschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
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.nonono
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methodsJDBC
Native API
GraphQL
RESTful HTTP API
WebSocket
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Deno
Go
JavaScript (Node.js)
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
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.yesnoyes
User concepts infoAccess controlyesyes, based on authentication and database rulesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBSurrealDBVertica infoOpenText™ Vertica™Yaacomo
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
Apache IoTDBSurrealDBVertica infoOpenText™ Vertica™Yaacomo
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