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DBMS > ArcadeDB vs. BoltDB vs. CrateDB vs. Teradata Aster

System Properties Comparison ArcadeDB vs. BoltDB vs. CrateDB vs. Teradata Aster

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonBoltDB  Xexclude from comparisonCrateDB  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenAn embedded key-value store for Go.Distributed Database based on LucenePlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Key-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.80
Rank#215  Overall
#31  Key-value stores
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Websitearcadedb.comgithub.com/­boltdb/­boltcratedb.com
Technical documentationdocs.arcadedb.comcratedb.com/­docs
DeveloperArcade DataCrateTeradata
Initial release2021201320132005
Current releaseSeptember 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Sourcecommercial
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 languageJavaGoJava
Server operating systemsAll OS with a Java VMBSD
Linux
OS X
Solaris
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language, no joinsnoyes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJavaGo.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
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnouser defined functions (Javascript)R packages
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneConfigurable replication on table/partition-levelyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes inforelationship in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.nonono
User concepts infoAccess controlnorights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
ArcadeDBBoltDBCrateDBTeradata Aster
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
ArcadeDBBoltDBCrateDBTeradata Aster
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