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DBMS > GreptimeDB vs. JanusGraph vs. Vertica

System Properties Comparison GreptimeDB vs. JanusGraph vs. Vertica

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Editorial information provided by DB-Engines
NameGreptimeDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn open source Time Series DBMS built for increased scalability, high performance and efficiencyA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Cloud 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 modelTime Series DBMSGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegreptime.comjanusgraph.orgwww.vertica.com
Technical documentationdocs.greptime.comdocs.janusgraph.orgvertica.com/­documentation
DeveloperGreptime Inc.Linux Foundation; originally developed as Titan by AureliusOpenText infopreviously Micro Focus and Hewlett Packard
Initial release202220172005
Current release0.6.3, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageRustJavaC++
Server operating systemsAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeschema-free, schema definition possibleyesYes, 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 dateyesyesyes
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 indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsgRPC
HTTP API
JDBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC++
Erlang
Go
Java
JavaScript
Clojure
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresPythonyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)horizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-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 methodsnoyes infovia Faunus, a graph analytics engineno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlSimple rights management via user accountsUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GreptimeDBJanusGraph infosuccessor of TitanVertica infoOpenText™ Vertica™
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
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Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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Cost-based models and subscription-based models are both available. One license is...
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More resources
GreptimeDBJanusGraph infosuccessor of TitanVertica infoOpenText™ Vertica™
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