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DBMS > Apache Doris vs. BigObject vs. HugeGraph vs. Tarantool

System Properties Comparison Apache Doris vs. BigObject vs. HugeGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonBigObject  Xexclude from comparisonHugeGraph  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAnalytic DBMS for real-time computations and queriesA fast-speed and highly-scalable Graph DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedGraph DBMSDocument 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
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
bigobject.iogithub.com/­hugegraph
hugegraph.apache.org
www.tarantool.io
Technical documentationgithub.com/­apache/­doris/­wikidocs.bigobject.iohugegraph.apache.org/­docswww.tarantool.io/­en/­doc
DeveloperApache Software Foundation, originally contributed from BaiduBigObject, Inc.BaiduVK
Initial release2017201520182008
Current release1.2.2, February 20230.92.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache Version 2.0Open 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 languageJavaJavaC and C++
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
macOS
Unix
BSD
Linux
macOS
Data schemeyesyesyesFlexible 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.nononono
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoFull-featured ANSI SQL support
APIs and other access methodsJDBC
MySQL client
fluentd
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Open binary protocol
Supported programming languagesJavaGroovy
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsLuaasynchronous Gremlin script jobsLua, C and SQL stored procedures
Triggersnononoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneyes 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 nodesnonenoneyes 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 methodsnonovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual 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 infoautomatically between fact table and dimension tablesyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes, 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.noyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardnoUsers, roles and permissionsAccess 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
Apache DorisBigObjectHugeGraphTarantool
DB-Engines blog posts

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

show all

Recent citations in the news

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