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DBMS > Apache Druid vs. atoti vs. EXASOL vs. Fujitsu Enterprise Postgres vs. Quasardb

System Properties Comparison Apache Druid vs. atoti vs. EXASOL vs. Fujitsu Enterprise Postgres vs. Quasardb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonatoti  Xexclude from comparisonEXASOL  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Distributed, high-performance timeseries database
Primary database modelRelational DBMS
Time Series DBMS
Object oriented DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitedruid.apache.orgatoti.iowww.exasol.comwww.postgresql.fastware.comquasar.ai
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.atoti.iowww.exasol.com/­resourceswww.postgresql.fastware.com/­product-manualsdoc.quasar.ai/­master
DeveloperApache Software Foundation and contributorsActiveViamExasolPostgreSQL Global Development Group, Fujitsu Australia Software Technologyquasardb
Initial release201220002009
Current release29.0.1, April 2024Fujitsu Enterprise Postgres 14, January 20223.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree versions availablecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++
Server operating systemsLinux
OS X
Unix
Linux
Windows
BSD
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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.nonono
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLSQL for queryingMultidimensional Expressions (MDX)yesyesSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.Net
JDBC
ODBC
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Lua
Python
R
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoPythonuser defined functionsuser defined functionsno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding, horizontal partitioningShardingpartitioning by range, list and by hashSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoTransient mode
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail
More information provided by the system vendor
Apache DruidatotiEXASOLFujitsu Enterprise PostgresQuasardb
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 DruidatotiEXASOLFujitsu Enterprise PostgresQuasardb
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