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DBMS > Apache Drill vs. Atos Standard Common Repository vs. CrateDB vs. GigaSpaces vs. Oracle Berkeley DB

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. CrateDB vs. GigaSpaces vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksDistributed Database based on LuceneHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsWidely used in-process key-value store
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsRelational DBMSGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitedrill.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comwww.gigaspaces.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdrill.apache.org/­docscratedb.com/­docsdocs.gigaspaces.com/­latest/­landing.htmldocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software FoundationAtos Convergence CreatorsCrateGigaspaces TechnologiesOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20122016201320001994
Current release1.20.3, January 2023170315.5, September 202018.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaJava, C++, .NetC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux
OS X
Windows
LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesoptionalyesyesno
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.noyesnono infoXML can be used for describing objects metadatayes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-99 for query and DML statementsyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
LDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Supported programming languagesC++All languages with LDAP bindings.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C++
Java
Python
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnouser defined functions (Javascript)yesno
Triggersnoyesnoyes, event driven architectureyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Read-after-write consistency on record level
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesnoyesyes
User concepts infoAccess controlDepending on the underlying data sourceLDAP bind authenticationrights management via user accountsRole-based access controlno
More information provided by the system vendor
Apache DrillAtos Standard Common RepositoryCrateDBGigaSpacesOracle Berkeley DB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Apache DrillAtos Standard Common RepositoryCrateDBGigaSpacesOracle Berkeley DB
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