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DBMS > Apache Druid vs. EDB Postgres vs. Google Cloud Spanner vs. HugeGraph

System Properties Comparison Apache Druid vs. EDB Postgres vs. Google Cloud Spanner vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument store
Spatial 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
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitedruid.apache.orgwww.enterprisedb.comcloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designwww.enterprisedb.com/­docscloud.google.com/­spanner/­docshugegraph.apache.org/­docs
DeveloperApache Software Foundation and contributorsEnterpriseDBGoogleBaidu
Initial release2012200520172018
Current release29.0.1, April 202414, December 20210.9
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoBSD for PostgreSQL-componentscommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava
Server operating systemsLinux
OS X
Unix
Linux
Windows
hostedLinux
macOS
Unix
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL for queryingyes infostandard with numerous extensionsyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noasynchronous Gremlin script jobs
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning infoby hash, list or rangeShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replicationMulti-source replication with 3 replicas for regional instances.yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions

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More resources
Apache DruidEDB PostgresGoogle Cloud SpannerHugeGraph
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