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DBMS > EsgynDB vs. Infobright vs. LevelDB vs. Spark SQL

System Properties Comparison EsgynDB vs. Infobright vs. LevelDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonInfobright  Xexclude from comparisonLevelDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnignitetech.com/­softwarelibrary/­infobrightdbgithub.com/­google/­leveldbspark.apache.org/­sql
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynIgnite Technologies Inc.; formerly InfoBright Inc.GoogleApache Software Foundation
Initial release2015200520112014
Current release1.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaCC++Scala
Server operating systemsLinuxLinux
Windows
Illumos
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesno infoKnowledge Grid Technology used insteadnono
SQL infoSupport of SQLyesyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnono

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EsgynDBInfobrightLevelDBSpark SQL
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