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DBMS > EXASOL vs. GreptimeDB vs. JaguarDB vs. Vertica

System Properties Comparison EXASOL vs. GreptimeDB vs. JaguarDB vs. Vertica

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGreptimeDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.An open source Time Series DBMS built for increased scalability, high performance and efficiencyPerformant, highly scalable DBMS for AI and IoT applicationsCloud 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 DBMSTime Series DBMSKey-value store
Vector DBMS
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#138  Overall
#64  Relational DBMS
Score0.09
Rank#343  Overall
#31  Time Series DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
#16  Vector DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.exasol.comgreptime.comwww.jaguardb.comwww.vertica.com
Technical documentationwww.exasol.com/­resourcesdocs.greptime.comwww.jaguardb.com/­support.htmlvertica.com/­documentation
DeveloperExasolGreptime Inc.DataJaguar, Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2000202220152005
Current release3.3 July 202312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoGPL V3.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono 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 languageRustC++ infothe server part. Clients available in other languagesC++
Server operating systemsAndroid
Docker
FreeBSD
Linux
macOS
Windows
LinuxLinux
Data schemeyesschema-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 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.nononono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC
HTTP API
JDBC
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Lua
Python
R
C++
Erlang
Go
Java
JavaScript
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsPythonnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source 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 methodsyes infoHadoop integrationnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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-standardSimple rights management via user accountsrights management via user accountsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EXASOLGreptimeDBJaguarDBVertica infoOpenText™ Vertica™
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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More resources
EXASOLGreptimeDBJaguarDBVertica infoOpenText™ Vertica™
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