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DBMS > Drizzle vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner vs. Hazelcast

System Properties Comparison Drizzle vs. Fujitsu Enterprise Postgres vs. Google Cloud Spanner vs. Hazelcast

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHazelcast  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.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 widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Websitewww.postgresql.fastware.comcloud.google.com/­spannerhazelcast.com
Technical documentationwww.postgresql.fastware.com/­product-manualscloud.google.com/­spanner/­docshazelcast.org/­imdg/­docs
DeveloperDrizzle project, originally started by Brian AkerPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleHazelcast
Initial release200820172008
Current release7.2.4, September 2012Fujitsu Enterprise Postgres 14, January 20225.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemsFreeBSD
Linux
OS X
Linux
Windows
hostedAll OS with a Java VM
Data schemeyesyesyesschema-free
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 infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesyes infoQuery statements complying to ANSI 2011SQL-like query language
APIs and other access methodsJDBCADO.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
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoEvent Listeners, Executor Services
Triggersno infohooks for callbacks inside the server can be used.yesnoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication with 3 replicas for regional instances.yes infoReplicated Map
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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationone or two-phase-commit; repeatable reads; read commited
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.noyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess 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
DrizzleFujitsu Enterprise PostgresGoogle Cloud SpannerHazelcast
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