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DBMS > EJDB vs. FaunaDB vs. Vertica

System Properties Comparison EJDB vs. FaunaDB vs. Vertica

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonFaunaDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Strongly consistent database capable of global horizontal scale with a focus on operational simplicityColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelDocument storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#260  Overall
#35  Document stores
Score0.95
Rank#154  Overall
#23  Document stores
#12  Graph DBMS
#75  Relational DBMS
#9  Time Series DBMS
Score20.75
Rank#30  Overall
#17  Relational DBMS
Websiteejdb.orgfauna.comwww.vertica.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.fauna.comwww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperSoftmotionsFauna, Inc.Vertica / Micro Focus infoprior to that Hewlett Packard
Initial release201220142005
Current releaseVertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemsserver-lessLinuxLinux
Data schemeschema-freeschema-freeyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idnoyes
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.noyes
Secondary indexesnoyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLnonoyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsin-process shared libraryRESTful HTTP APIADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnouser defined functionsyes
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoconsistent hashingSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMasterlessMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.no
User concepts infoAccess controlnoIdentity management, authentication, and access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EJDBFaunaDBVertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» 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 available
» more

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More resources
EJDBFaunaDBVertica infoVertica Analytics Platform
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