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DBMS > Apache Druid vs. BigObject vs. Google Cloud Datastore vs. RisingWave vs. SwayDB

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

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRisingWave  Xexclude from comparisonSwayDB  Xexclude from comparison
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 PlatformA distributed RDBMS for stream processing, wire-compatible with PostgreSQLAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infoa hierachical model (tree) can be imposedDocument storeRelational DBMSKey-value store
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
Score0.58
Rank#242  Overall
#111  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgbigobject.iocloud.google.com/­datastorewww.risingwave.com/­databaseswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.bigobject.iocloud.google.com/­datastore/­docsdocs.risingwave.com/­docs/­current/­intro
DeveloperApache Software Foundation and contributorsBigObject, Inc.GoogleRisingWave LabsSimer Plaha
Initial release20122015200820222018
Current release29.0.1, April 20241.2, September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercialOpen Source infoApache Version 2.0Open Source infoGNU Affero GPL V3.0
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 languageJavaRustScala
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)
hostedDocker
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereStandard SQL-types and JSONno
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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query language (GQL)yesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
fluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoLuausing Google App EngineUDFs in Python or Javano
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
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 Consistency
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 TransactionsnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.noyesnoyesyes
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)Users and Rolesno

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More resources
Apache DruidBigObjectGoogle Cloud DatastoreRisingWaveSwayDB
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