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DBMS > EJDB vs. IRONdb vs. Vertica

System Properties Comparison EJDB vs. IRONdb vs. Vertica

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonIRONdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityCloud 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 storeTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.circonus.com/solutions/time-series-database/www.vertica.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.circonus.com/irondb/category/getting-startedvertica.com/­documentation
DeveloperSoftmotionsCirconus LLC.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220172005
Current releaseV0.10.20, January 201812.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercial 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 languageCC and C++C++
Server operating systemsserver-lessLinuxLinux
Data schemeschema-freeschema-freeYes, 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 dateyes infostring, integer, double, bool, date, object_idyes infotext, numeric, histogramsyes
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.nono
Secondary indexesnonoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsin-process shared libraryHTTP APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, in Luayes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter awareMulti-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 methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EJDBIRONdbVertica infoOpenText™ Vertica™
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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
EJDBIRONdbVertica infoOpenText™ Vertica™
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