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DBMS > DuckDB vs. GeoSpock vs. Hazelcast vs. Tarantool

System Properties Comparison DuckDB vs. GeoSpock vs. Hazelcast vs. Tarantool

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Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonHazelcast  Xexclude from comparisonTarantool  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSSpatial and temporal data processing engine for extreme data scaleA widely adopted in-memory data gridIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Secondary database modelsTime Series DBMSDocument store infoJSON support with IMDG 3.12Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websiteduckdb.orggeospock.comhazelcast.comwww.tarantool.io
Technical documentationduckdb.org/­docshazelcast.org/­imdg/­docswww.tarantool.io/­en/­doc
DeveloperGeoSpockHazelcastVK
Initial release201820082008
Current release1.0.0, June 20242.0, September 20195.3.6, November 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, JavascriptJavaC and C++
Server operating systemsserver-lesshostedAll OS with a Java VMBSD
Linux
macOS
Data schemeyesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 infothe object must implement a serialization strategyno
Secondary indexesyestemporal, categoricalyesyes
SQL infoSupport of SQLyesANSI SQL for query only (using Presto)SQL-like query languageFull-featured ANSI SQL support
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JDBCJCache
JPA
Memcached protocol
RESTful HTTP API
Open binary protocol
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoyes infoEvent Listeners, Executor ServicesLua, C and SQL stored procedures
Triggersnonoyes infoEventsyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated MapAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmCasual 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
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoone or two-phase-commit; repeatable reads; read commitedACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnoAccess rights for users can be defined per tableRole-based access controlAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
DuckDBGeoSpockHazelcastTarantool
DB-Engines blog posts

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

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