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DBMS > Apache Druid vs. BigObject vs. Google Cloud Datastore vs. SwayDB vs. Teradata Aster

System Properties Comparison Apache Druid vs. BigObject vs. Google Cloud Datastore vs. SwayDB vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSwayDB  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.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for real-time computations and queriesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storagePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infoa hierachical model (tree) can be imposedDocument storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgbigobject.iocloud.google.com/­datastoreswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.bigobject.iocloud.google.com/­datastore/­docs
DeveloperApache Software Foundation and contributorsBigObject, Inc.GoogleSimer PlahaTeradata
Initial release20122015200820182005
Current release29.0.1, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercialOpen Source infoGNU Affero GPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemsLinux
OS X
Unix
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-freeFlexible 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 dateyesyesyes, details herenoyes
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.nonononoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query language (GQL)noyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
fluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Kotlin
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoLuausing Google App EnginenoR packages
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneMulti-source replication using Paxosnoneyes 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 methodsnonoyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache DruidBigObjectGoogle Cloud DatastoreSwayDBTeradata Aster
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