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DBMS > Amazon DynamoDB vs. Apache Phoenix vs. HugeGraph vs. Tarantool

System Properties Comparison Amazon DynamoDB vs. Apache Phoenix vs. HugeGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonHugeGraph  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseA fast-speed and highly-scalable Graph DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument store
Key-value store
Relational DBMSGraph 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
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websiteaws.amazon.com/­dynamodbphoenix.apache.orggithub.com/­hugegraph
hugegraph.apache.org
www.tarantool.io
Technical documentationdocs.aws.amazon.com/­dynamodbphoenix.apache.orghugegraph.apache.org/­docswww.tarantool.io/­en/­doc
DeveloperAmazonApache Software FoundationBaiduVK
Initial release2012201420182008
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.92.10.0, May 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2.0Open 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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemshostedLinux
Unix
Windows
Linux
macOS
Unix
BSD
Linux
macOS
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesyesFlexible 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 indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnoyesnoFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIJDBCJava API
RESTful HTTP API
TinkerPop Gremlin
Open binary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Groovy
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnouser defined functionsasynchronous Gremlin script jobsLua, C and SQL stored procedures
Triggersyes infoby integration with AWS Lambdanonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes 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 nodesyesMulti-source replication
Source-replica replication
yes 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual 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 integritynonoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDACIDACID, 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 persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers, 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
Amazon DynamoDBApache PhoenixHugeGraphTarantool
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