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DBMS > Apache Druid vs. Firebolt vs. Tarantool vs. TimescaleDB

System Properties Comparison Apache Druid vs. Firebolt vs. Tarantool vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFirebolt  Xexclude from comparisonTarantool  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extensionRelational 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#134  Overall
#62  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitedruid.apache.orgwww.firebolt.iowww.tarantool.iowww.timescale.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.firebolt.iowww.tarantool.io/­en/­docdocs.timescale.com
DeveloperApache Software Foundation and contributorsFirebolt Analytics Inc.VKTimescale
Initial release2012202020082017
Current release29.0.1, April 20242.10.0, May 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C
Server operating systemsLinux
OS X
Unix
hostedBSD
Linux
macOS
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimenumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyesFull-featured ANSI SQL supportyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.Net
ODBC
RESTful HTTP API
Open binary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoLua, C and SQL stored proceduresuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesdepending on storage layerAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
Apache DruidFireboltTarantoolTimescaleDB
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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