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DBMS > Apache Phoenix vs. GreptimeDB vs. Hazelcast vs. LMDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. GreptimeDB vs. Hazelcast vs. LMDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGreptimeDB  Xexclude from comparisonHazelcast  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn open source Time Series DBMS built for increased scalability, high performance and efficiencyA widely adopted in-memory data gridA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSKey-value storeKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.06
Rank#352  Overall
#33  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.99
Rank#125  Overall
#21  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orggreptime.comhazelcast.comwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.greptime.comhazelcast.org/­imdg/­docswww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGreptime Inc.HazelcastSymasApache Software Foundation
Initial release20142022200820112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 20230.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRustJavaCScala
Server operating systemsLinux
Unix
Windows
Android
Docker
FreeBSD
Linux
macOS
Windows
All OS with a Java VMLinux
Unix
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-free, schema definition possibleschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLyesyesSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC
HTTP API
JDBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Erlang
Go
Java
JavaScript
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsPythonyes infoEvent Listeners, Executor Servicesnono
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancySimple rights management via user accountsRole-based access controlnono
More information provided by the system vendor
Apache PhoenixGreptimeDBHazelcastLMDBSpark SQL
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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Apache PhoenixGreptimeDBHazelcastLMDBSpark SQL
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