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DBMS > Apache Druid vs. Faircom EDGE vs. Google Cloud Datastore vs. TigerGraph

System Properties Comparison Apache Druid vs. Faircom EDGE vs. Google Cloud Datastore vs. TigerGraph

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Document storeGraph 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
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-edgecloud.google.com/­datastorewww.tigergraph.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­datastore/­docsdocs.tigergraph.com
DeveloperApache Software Foundation and contributorsFairCom CorporationGoogle
Initial release2012197920082017
Current release29.0.1, April 2024V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoRestricted, free version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C++
Server operating systemsLinux
OS X
Unix
Android
Linux infoARM, x86
Raspbian
Windows
hostedLinux
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes, 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.noyesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingyes infoANSI SQL queriesSQL-like query language (GQL)SQL-like query language (GSQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++using Google App Engineyes
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate 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.
Foreign keys infoReferential integritynoyes infowhen using SQLyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Apache DruidFaircom EDGE infoformerly c-treeEDGEGoogle Cloud DatastoreTigerGraph
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