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DBMS > atoti vs. HBase vs. QuestDB vs. Spark SQL

System Properties Comparison atoti vs. HBase vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Wide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSWide column storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#242  Overall
#10  Object oriented DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iohbase.apache.orgquestdb.iospark.apache.org/­sql
Technical documentationdocs.atoti.iohbase.apache.org/­book.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology IncApache Software Foundation
Initial release200820142014
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava (Zero-GC), C++, RustScala
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes
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 indexesnonono
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infoCoprocessors in Javanono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno
More information provided by the system vendor
atotiHBaseQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
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