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DBMS > Graph Engine vs. RavenDB vs. SQream DB vs. Tarantool

System Properties Comparison Graph Engine vs. RavenDB vs. SQream DB vs. Tarantool

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonRavenDB  Xexclude from comparisonSQream DB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOpen Source Operational and Transactional Enterprise NoSQL Document Databasea GPU-based, columnar RDBMS for big data analytics workloadsIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
Key-value store
Document storeRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score2.84
Rank#101  Overall
#18  Document stores
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.graphengine.ioravendb.netsqream.comwww.tarantool.io
Technical documentationwww.graphengine.io/­docs/­manualravendb.net/­docsdocs.sqream.comwww.tarantool.io/­en/­doc
DeveloperMicrosoftHibernating RhinosSQream TechnologiesVK
Initial release2010201020172008
Current release5.4, July 20222022.1.6, December 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoAGPL version 3, commercial license availablecommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC#C++, CUDA, Haskell, Java, ScalaC and C++
Server operating systems.NETLinux
macOS
Raspberry Pi
Windows
LinuxBSD
Linux
macOS
Data schemeyesschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesnoyes, ANSI Standard SQL Typesstring, 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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (RQL)yesFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
.Net
JDBC
ODBC
Open binary protocol
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesyesuser defined functions in PythonLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal and vertical partitioningSharding, 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 nodesMulti-source replicationnoneAsynchronous 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 methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate 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
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAuthorization levels configured per client per databaseAccess 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
Graph Engine infoformer name: TrinityRavenDBSQream DBTarantool
DB-Engines blog posts

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

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