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DBMS > Apache Druid vs. etcd vs. Google Cloud Spanner vs. Kdb

System Properties Comparison Apache Druid vs. etcd vs. Google Cloud Spanner vs. Kdb

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA distributed reliable key-value storeA 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.High performance Time Series DBMS
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMSTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websitedruid.apache.orgetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­spannerkx.com
Technical documentationdruid.apache.org/­docs/­latest/­designetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­spanner/­docscode.kx.com
DeveloperApache Software Foundation and contributorsGoogleKx Systems, a division of First Derivatives plc
Initial release201220172000 infokdb was released 2000, kdb+ in 2003
Current release29.0.1, April 20243.4, August 20193.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercialcommercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoq
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononoyes
Secondary indexesyesnoyesyes infotable attribute 'grouped'
SQL infoSupport of SQLSQL for queryingnoyes infoQuery statements complying to ANSI 2011SQL-like query language (q)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresnononouser defined functions
Triggersnoyes, watching key changesnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication with 3 replicas for regional instances.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 systemnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts
More information provided by the system vendor
Apache DruidetcdGoogle Cloud SpannerKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache DruidetcdGoogle Cloud SpannerKdb
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