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DBMS > Apache Impala vs. EsgynDB vs. Fujitsu Enterprise Postgres vs. GridGain vs. Sequoiadb

System Properties Comparison Apache Impala vs. EsgynDB vs. Fujitsu Enterprise Postgres vs. GridGain vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGridGain  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.GridGain is an in-memory computing platform, built on Apache IgniteNewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Document store
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websiteimpala.apache.orgwww.esgyn.cnwww.postgresql.fastware.comwww.gridgain.comwww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manualswww.gridgain.com/­docs/­index.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGridGain Systems, Inc.Sequoiadb Ltd.
Initial release2013201520072013
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaCJava, C++, .NetC++
Server operating systemsLinuxLinuxLinux
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes infooid, date, timestamp, binary, regex
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.nonoyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)JavaScript
Triggersnonoyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersSource-replica replicationyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardSecurity Hooks for custom implementationssimple password-based access control
More information provided by the system vendor
Apache ImpalaEsgynDBFujitsu Enterprise PostgresGridGainSequoiadb
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Apache ImpalaEsgynDBFujitsu Enterprise PostgresGridGainSequoiadb
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