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DBMS > atoti vs. BigchainDB vs. CrateDB vs. OrientDB

System Properties Comparison atoti vs. BigchainDB vs. CrateDB vs. OrientDB

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBigchainDB  Xexclude from comparisonCrateDB  Xexclude from comparisonOrientDB  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.BigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDistributed Database based on LuceneMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelObject oriented DBMSDocument storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Graph DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.25
Rank#89  Overall
#16  Document stores
#6  Graph DBMS
#13  Key-value stores
Websiteatoti.iowww.bigchaindb.comcratedb.comorientdb.org
Technical documentationdocs.atoti.iobigchaindb.readthedocs.io/­en/­latestcratedb.com/­docswww.orientdb.com/­docs/­last/­index.html
DeveloperActiveViamCrateOrientDB LTD; CallidusCloud; SAP
Initial release201620132010
Current release3.2.29, March 2024
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoAGPL v3Open SourceOpen Source infoApache version 2
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.
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 languageJavaPythonJavaJava
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java JDK (>= JDK 6)
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or datenoyesyes
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 indexesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query language, no joins
APIs and other access methodsCLI Client
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.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
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresPythonuser defined functions (Javascript)Java, Javascript
TriggersnoHooks
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorConfigurable replication on table/partition-levelMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integritynonoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesrights management via user accountsAccess rights for users and roles; record level security configurable
More information provided by the system vendor
atotiBigchainDBCrateDBOrientDB
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
atotiBigchainDBCrateDBOrientDB
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