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DBMS > Atos Standard Common Repository vs. Databricks vs. GigaSpaces vs. QuestDB

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. GigaSpaces vs. QuestDB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonQuestDB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA high performance open source SQL database for time series data
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Secondary database modelsGraph DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comwww.gigaspaces.comquestdb.io
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlquestdb.io/­docs
DeveloperAtos Convergence CreatorsDatabricksGigaspaces TechnologiesQuestDB Technology Inc
Initial release2016201320002014
Current release170315.5, September 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetJava (Zero-GC), C++, Rust
Server operating systemsLinuxhostedLinux
macOS
Solaris
Windows
Linux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateoptionalyesyes
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.yesyesno infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesno
SQL infoSupport of SQLnowith Databricks SQLSQL-99 for query and DML statementsSQL with time-series extensions
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
.Net
C++
Java
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesno
Triggersyesyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes infothrough memory mapped files
User concepts infoAccess controlLDAP bind authenticationRole-based access control
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksGigaSpacesQuestDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational 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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