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DBMS > Datomic vs. HugeGraph vs. SurrealDB vs. Tarantool

System Properties Comparison Datomic vs. HugeGraph vs. SurrealDB vs. Tarantool

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHugeGraph  Xexclude from comparisonSurrealDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA fast-speed and highly-scalable Graph DBMSA fully ACID transactional, developer-friendly, multi-model DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSGraph DBMSDocument store
Graph DBMS
Document store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.datomic.comgithub.com/­hugegraph
hugegraph.apache.org
surrealdb.comwww.tarantool.io
Technical documentationdocs.datomic.comhugegraph.apache.org/­docssurrealdb.com/­docswww.tarantool.io/­en/­doc
DeveloperCognitectBaiduSurrealDB LtdVK
Initial release2012201820222008
Current release1.0.7075, December 20230.9v1.5.0, May 20242.10.0, May 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0Open SourceOpen 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 languageJava, ClojureJavaRustC and C++
Server operating systemsAll OS with a Java VMLinux
macOS
Unix
Linux
macOS
Windows
BSD
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.nonono
Secondary indexesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnonoSQL-like query languageFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
GraphQL
RESTful HTTP API
WebSocket
Open binary protocol
Supported programming languagesClojure
Java
Groovy
Java
Python
Deno
Go
JavaScript (Node.js)
Rust
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infoTransaction Functionsasynchronous Gremlin script jobsLua, C and SQL stored procedures
TriggersBy using transaction functionsnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding, 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 nodesnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBaseAsynchronous 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 methodsnovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 integritynoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID, 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 persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnoUsers, roles and permissionsyes, based on authentication and database rulesAccess 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
DatomicHugeGraphSurrealDBTarantool
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Data processing speed and reliability: in-memory synchronous replication
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