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DBMS > Apache Pinot vs. ArcadeDB vs. BigchainDB vs. Google Cloud Datastore vs. Ingres

System Properties Comparison Apache Pinot vs. ArcadeDB vs. BigchainDB vs. Google Cloud Datastore vs. Ingres

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonArcadeDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMS
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websitepinot.apache.orgarcadedb.comwww.bigchaindb.comcloud.google.com/­datastorewww.actian.com/­databases/­ingres
Technical documentationdocs.pinot.apache.orgdocs.arcadedb.combigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.actian.com/­ingres
DeveloperApache Software Foundation and contributorsArcade DataGoogleActian Corporation
Initial release20152021201620081974 infooriginally developed at University Berkely in early 1970s
Current release1.0.0, September 2023September 202111.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoAGPL v3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaPythonC
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VMLinuxhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes, details hereyes
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.nononono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language, no joinsnoSQL-like query language (GQL)yes
APIs and other access methodsJDBCJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
CLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesGo
Java
Python
JavaGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes
TriggersCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication using PaxosIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integrityyes inforelationship in graphsnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache PinotArcadeDBBigchainDBGoogle Cloud DatastoreIngres
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