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DBMS > Apache Phoenix vs. HugeGraph vs. OpenTSDB vs. Tarantool

System Properties Comparison Apache Phoenix vs. HugeGraph vs. OpenTSDB vs. Tarantool

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHugeGraph  Xexclude from comparisonOpenTSDB  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA fast-speed and highly-scalable Graph DBMSScalable Time Series DBMS based on HBaseIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSGraph DBMSTime Series 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score1.68
Rank#146  Overall
#12  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitephoenix.apache.orggithub.com/­hugegraph
hugegraph.apache.org
opentsdb.netwww.tarantool.io
Technical documentationphoenix.apache.orghugegraph.apache.org/­docsopentsdb.net/­docs/­build/­html/­index.htmlwww.tarantool.io/­en/­doc
DeveloperApache Software FoundationBaiducurrently maintained by Yahoo and other contributorsVK
Initial release2014201820112008
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.92.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoLGPLOpen 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 languageJavaJavaJavaC and C++
Server operating systemsLinux
Unix
Windows
Linux
macOS
Unix
Linux
Windows
BSD
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesnumeric data for metrics, strings for tagsstring, 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 indexesyesyes infoalso supports composite index and range indexnoyes
SQL infoSupport of SQLyesnonoFull-featured ANSI SQL support
APIs and other access methodsJDBCJava API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Telnet API
Open binary protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Groovy
Java
Python
Erlang
Go
Java
Python
R
Ruby
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsasynchronous Gremlin script jobsnoLua, 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 nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infobased on 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 nodesMulti-source replication
Source-replica replication
yes infodepending on used storage backend, e.g. Cassandra and HBaseselectable replication factor infobased on 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 methodsHadoop integrationvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency infobased on HBaseCasual 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 graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, 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.yesyesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers, roles and permissionsnoAccess 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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Apache PhoenixHugeGraphOpenTSDBTarantool
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